Download What Is So Special About Male Adolescent Sexual Offending?

Psychological Bulletin
2010, Vol. 136, No. 4, 526 –575
© 2010 American Psychological Association
0033-2909/10/$12.00 DOI: 10.1037/a0019700
What Is So Special About Male Adolescent Sexual Offending? A Review
and Test of Explanations Through Meta-Analysis
Michael C. Seto
Martin L. Lalumière
Royal Ottawa Health Care Group
University of Lethbridge
We tested special and general explanations of male adolescent sexual offending by conducting a meta-analysis
of 59 independent studies comparing male adolescent sex offenders (n ⫽ 3,855) with male adolescent non-sex
offenders (n ⫽ 13,393) on theoretically derived variables reflecting general delinquency risk factors (antisocial
tendencies), childhood abuse, exposure to violence, family problems, interpersonal problems, sexuality,
psychopathology, and cognitive abilities. The results did not support the notion that adolescent sexual
offending can be parsimoniously explained as a simple manifestation of general antisocial tendencies.
Adolescent sex offenders had much less extensive criminal histories, fewer antisocial peers, and fewer
substance use problems compared with non-sex offenders. Special explanations suggesting a role for sexual
abuse history, exposure to sexual violence, other abuse or neglect, social isolation, early exposure to sex or
pornography, atypical sexual interests, anxiety, and low self-esteem received support. Explanations focusing
on attitudes and beliefs about women or sexual offending, family communication problems or poor parent–
child attachment, exposure to nonsexual violence, social incompetence, conventional sexual experience, and
low intelligence were not supported. Ranked by effect size, the largest group difference was obtained for
atypical sexual interests, followed by sexual abuse history, and, in turn, criminal history, antisocial associations, and substance abuse. We discuss the implications of the findings for theory development, as well as for
the assessment, treatment, and prevention of adolescent sexual offending.
Keywords: adolescent sexual offending, general delinquency, atypical sexual interests, sexual abuse,
meta-analysis
Many resources have been devoted to the prevention of sexual
crimes and the management of sex offenders in the past 20 years.
Sex offender registration and community notification laws were
introduced in the 1990s, civil commitment proceedings against
high-risk sex offenders re-emerged during the same time period,
and specialized sex offender treatment programs have proliferated
in correctional and mental health settings. Social policies and
associated clinical practices have benefited from major improve-
ments in clinicians’ ability to assess the likelihood of reoffending
of individual sex offenders, but less progress has been made in
developing successful interventions to reduce such likelihood (for
reviews, see Lalumière, Harris, Quinsey, & Rice, 2005; Seto,
2008). Assessment, treatment, and policy efforts could all benefit
from a better understanding of the etiology of sexual offending.
Early work on the causes of sexual offending focused almost
exclusively on adult offenders.1 Many investigators are now rec-
Michael C. Seto, Royal Ottawa Health Care Group, Ottawa, Ontario,
Canada; Martin L. Lalumière, Department of Psychology, University of
Lethbridge, Lethbridge, Alberta, Canada.
An earlier version of this meta-analysis was presented at the 23rd annual
conference of the Association for the Treatment of Sexual Abusers in 2004.
Part of the results regarding criminal history and conduct problems were
published as a book chapter (Seto & Lalumière, 2006).
We would like to thank Judith Becker, James Cantor, Meredith Chivers,
Amanda Fanniff, Tracey Skilling, and Kelly Suschinsky for their helpful
comments on earlier versions of this article. We would like to especially
acknowledge Mark Chaffin, Grant Harris, Vern Quinsey, and Jim Worling
for their detailed comments and suggestions for improvement.
We were able to find current contact information for 48 of the 57 (van
Wijk was the first author of three studies) first authors (or second
authors, if the first author was unavailable) and the first author’s
academic advisor, in the case of master’s theses or doctoral dissertations, for the studies we examined in this meta-analysis. Twenty-three
of the 48 first authors or academic advisors we contacted responded to
our e-mails or letter. We would like to thank Mary Davis-Rosanbalm,
Kevin Epps, Paul Frick, Gordon Hall, Daniel Hilliker, Clive Hollin,
Melissa Jonson-Reid, Brian Jory, Alejandro Leguizamo, Carin Ness,
Hank Schneider, John Sivley, Derek Truscott, Ineke Way, Anton van
Wijk, Jeff Wong, and Barry Zakireh for checking the results we
reported for their studies, and for their comments. We are also grateful
to Michael Miner for providing unpublished data and to Dustin Pardini
for conducting additional analyses to determine if we could use data
from van Wijk, Loeber, et al. (2005). We apologize to anyone we have
missed from this list.
Correspondence concerning this article should be addressed to Michael
C. Seto, Integrated Forensic Program, Brockville Mental Health Centre,
Royal Ottawa Health Care Group, Brockville, Ontario, Canada, K6V 5W7,
or to Martin L. Lalumière, Department of Psychology, University of
Lethbridge, Lethbridge, Alberta, Canada, T1K 3M4. E-mail: michael.seto@
rohcg.on.ca or [email protected]
1
Most research has also focused on male offenders, at least in part
because the large majority of sexual offenses are committed by males
(Steffensmeier, Zhong, Ackerman, Schwartz, & Agha, 2006). Most of the
research cited in this review, and all of the theories, have focused on
offenses committed by males, either against female peers or adults or
against either boys or girls.
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ognizing that the study of adolescent offenders might offer great
promise for understanding the onset and course of sexual offending. Some adult sex offenders report committing their first sexual
offense before the age of 18 years (Abel, Osborn, & Twigg, 1993),
and some adolescent sex offenders began engaging in problematic
sexual behavior, including coercive sexual behavior, in childhood
(Burton, 2000). Many adolescent sex offenders desist from further
sexual offending, but at least 15% go on to commit detected sexual
offenses within an average of five years of opportunity (Caldwell,
2002; Worling & Långström, 2006).
Theoretical explanations of adolescent sexual offending have
tended to focus on offense-specific factors, that is, on causes that
are thought to be uniquely or primarily relevant to sexual crimes.
Thus, except for a minority who are thought to commit sexual
offenses as part of a broader pattern of delinquency, adolescent sex
offenders are viewed as a distinct group of offenders whose sexual
offenses are explained by special factors that differ from the
factors that explain the offenses of other juvenile delinquents (e.g.,
Becker, 1990, 1998; Worling & Långström, 2006). This has led to
statements such as the following from the National Adolescent
Perpetrator Network (1993): “Sexually abusive youth require a
specialized response from the justice system which is different
from other delinquent populations” (p. 86). An offense-specific
view is also common in the literature on adult sexual offending
(e.g., Ward, Polaschek, & Beech, 2006). We begin with a brief
review of theories of sexual offending and then describe the
rationale for the present quantitative review.
Theories of Sexual Offending
In their review of the literature on adolescent sexual offending,
Davis and Leitenberg (1987) noted that clinicians have suggested
that such factors as poor social skills, fear of rejection and anger
toward women, low self-esteem, feelings of personal inadequacy,
having been sexually abused, exposure to violence, and atypical
sexual interests may have causal impact. Drawing from and extending these clinical impressions, different multifactorial theories
have been proposed to explain adult, and subsequently adolescent,
sexual offending and to distinguish them from other kinds of
offending (for recent reviews see Barbaree & Langton, 2006;
Stinson, Sales, & Becker, 2008; Ward et al., 2006; for more
specific theories on sexual offending against children, see Finkelhor, 1984; Seto, 2008; Ward & Siegert, 2002; and for more
specific theories on sexual offending against women, see Lalumière et al., 2005; Malamuth, Sockloskie, Koss, & Tanaka, 1991).
The most prominent multifactorial theories of sexual offending
are briefly described below, in chronological order of publication.
Although originally formulated to explain adult sexual offending,
these multifactorial theories can provide a useful framework for
studying adolescent sexual offending because they are implicitly
developmental in some aspects (e.g., the effects of parent– child
attachment or early adverse experiences). These theories are sometimes vague about the specific predictions that one could make
regarding differences between sex offenders and other types of
offenders, but, where possible, we derive testable predictions.
Additional predictions about the role that individual variables play
in explaining adolescent sexual offending are presented later. We
do not discuss theories that have been developed to specifically
explain sexual offending against children or sexual offending
527
against peers or adults, because the studies we review in this
meta-analysis do not allow us to adequately test theories that
distinguish sexual offending according to victim age. We do,
however, examine sexual victim age as a moderator of group
differences when there are sufficient studies.
Marshall and Barbaree (1990) described a theory of sexual
offending that suggests that adverse early experiences (especially
child abuse and neglect) can disrupt the development of inhibitory
control (self-regulation skills) over normal aggressive tendencies
and sex drive. Adverse early experiences can also disrupt the
development of healthy attachment and social skills. These interpersonal problems, in turn, impede the formation of relationships
with peers and thus increase the likelihood that the individual will
sexually coerce peers or adults or will engage in sexual contacts
with younger children. Adolescence, especially early adolescence,
is seen as a critical time period in this theory because an at-risk
individual typically begins experiencing greater sex drive as a
result of entering puberty yet is less able to fulfill this in socially
acceptable ways. In addition, sexual arousal from contacts with
children or coercive sex is conditioned by the reward of sexual
gratification, as well as by the impact of sexual arousal and orgasm
on negative mood, both through the sexual offenses and later
masturbation to fantasies about the offenses.
Marshall and Barbaree’s (1990) theory suggests that sex offenders should differ from other offenders on measures of child abuse
and neglect, social skills deficits, self-regulation problems, and
sexual arousal to children or to coercive sex. One strength of this
theory is its developmental perspective, where childhood experiences influence adolescent development and behavior. Another
strength is its explicit hypothesis about the origins of sexual
arousal to children or to coercive sex. The theory is unclear,
however, about why individuals who are unsuccessful in peer
relationships choose sex with children or coercive sex rather than
options such as sex with prostitutes or masturbation to pornographic material or why difficulty in controlling aggressive tendencies is ever expressed through sexual contacts with children
among adolescents who are sexually attracted to peers or adults.
Hall and Hirschman (1991, 1992) identified four major factors
they thought could explain sexual offending: personality problems,
affective dysregulation, cognitions that justify sexual offending,
and sexual arousal to children or to sexual coercion. Hall and
Hirschman suggested that these factors could operate singly or in
combination but that a single factor typically was the most important for a particular individual. The quadripartite theory therefore
also suggests that there are different types of sex offenders; for
example, Hall and Hirschman suggested that offenders who were
primarily motivated by affective dysregulation would commit offenses opportunistically, use higher levels of violence, and commit
both sexual and nonsexual offenses.
A strength of Hall and Hirschman’s (1991, 1992) four-factor
theory is that it explicitly recognizes that there may be different
paths to sexual offending and different types of adolescent sex
offenders. However, the theory does not explain why one factor is
the most important for a particular individual or how the factors
interact to increase the likelihood of sexual offending. Hall and
Hirschman’s theory would predict that sex offenders would score
higher, on average, than other offenders on measures of personality problems, affective dysregulation, cognitions that justify sexual
offending, and sexual arousal to children or to sexual coercion.
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SETO AND LALUMIÈRE
In their integrative theory, Ward and Beech (2005) attempted to
integrate macro-level factors, such as evolutionary selection pressures and sociocultural factors, with individual factors such as
genetic predispositions, early experiences of sexual or physical
abuse, and individual differences in empathy, cognitive distortions,
emotional problems, interpersonal competence, and sexual interests. These researchers argued that clinical problems–in particular,
emotional problems, social difficulties, offense-supportive attitudes and beliefs, and sexual problems—arise from the interaction
of neuropsychological deficits and environmental triggers in particular sociocultural contexts. For example, they suggested that
emotional problems include mood problems resulting from deficits
in motivation and emotional dysregulation and impulsivity arising
from deficits in executive function. These emotional problems are
linked to sexual offending when individuals use sex as a means of
coping with negative emotional states (e.g., masturbation to sexual
fantasies). Triggers can include stressful events such as relationship conflict. Social difficulties are seen to be the result of problems with attachment, whereas sexual problems, including paraphilic sexual interests and excessive sexual drive or sexual
preoccupation, are seen as the product of attachment problems,
mood regulation problems, and offense-supportive attitudes and
beliefs. Ward and Beech did not discuss the origins of offensesupportive attitudes and beliefs except for noting that these cognitions are likely to form early and thereby serve as schemas for
the perception and integration of subsequent information about
women, children, or sex.
Ward and Beech (2005) suggested that their integrated theory
provides a conceptual framework to unify other theories and
generate novel research hypotheses. One strength of this theory is
that it seeks consilience in theorizing about sexual offending by
linking concepts from biology, psychology, and neuroscience.
However, this theory does not clearly define or specify the factors
that are thought to help explain sexual offending. For example, it
does not explain what genetic predispositions are involved, nor
does it explain how sexual problems such as paraphilic sexual
interests or excessive sexual drive or sexual preoccupation arise
from the other problems they considered. Using the examples
provided by Ward and Beech, one could predict that adolescent sex
offenders differ from other adolescent offenders on measures of
their sexual and physical abuse histories, emotional regulation
problems, personality traits such as impulsivity and empathy,
social skills, attitudes and beliefs about sexual offending, and
atypical sexual interests.
Comparing Theories of Sexual Offending
There are similarities across these theories of sexual offending.
All of them recognize a role for atypical sexual interests, and all of
them suggest that disinhibition, whether it is viewed as a trait (e.g.,
lack of empathy) or state (e.g., intoxication), increases the likelihood that someone will commit a sexual offense. The theories
differ in whether all of the factors are thought to play a role or if
a subset, or even a single factor, is sufficient to lead to sexual
offending. Finally, Marshall and Barbaree (1990) and Ward and
Beech (2005) present developmental perspectives, such that experiences and processes in childhood and adolescence lead to a
greater likelihood of sexual offending as an adolescent or adult,
respectively. As we discuss later, these multifactorial theories
include individual factors that have been emphasized in special
explanations of adolescent sexual offending.
Ward et al. (2006) have reviewed and critiqued these theories in
greater detail. All of the theories have limitations according to the
criteria of unifying power, internal consistency, ability to predict
future behavior, heuristic value, falsifiability, or parsimony. A
particular concern is the extent to which these theories can be
empirically tested, because many concepts are not clearly operationalized (e.g., “personality problems”) or because it is sometimes
unclear what specific and testable predictions the theorists themselves make. An additional concern is the extent to which these
theories, developed to explain adult sexual offending, might apply
to adolescent sexual offending. In this meta-analysis, we have
operationalized and tested aspects of these theories using comparisons of adolescent sex and non-sex offenders.
Methodological Considerations
Davis and Leitenberg (1987) highlighted a number of methodological problems in the adolescent sex offender literature more
than 20 years ago. They noted that the studies they reviewed were
predominantly descriptive, did not include suitable comparison
groups of adolescents without a sexual offense history, did not use
standardized measures, and combined different types of sex offenders. Indeed, Davis and Leitenberg succinctly articulated the
primary rationale for the present meta-analysis: “Studies of the
characteristics of adolescent sex offenders are ultimately concerned with the basic question of why some adolescents commit
sexual crimes and others do not” (p. 420).
Reviewing the research published since Davis and Leitenberg’s
(1987) review, it is still true that the reliability and validity of
many study measures has not been established, that many studies
rely on self-report, that studies do not always include suitable
comparison groups, and that most studies are cross-sectional in
nature, limiting the causal inferences that can be made. Moreover,
the majority of studies are of adolescents held in custody (either
incarcerated at detention facilities or placed in residential treatment centers) and recruited from similar but different settings. At
the same time, there now exist studies examining specific factors
identified by Davis and Leitenberg as candidate causes of adolescent sexual offending but for which no empirical evidence existed
when they completed their review.
Purpose of this Quantitative Review
Despite the conceptual and methodological issues that have
been identified regarding the adolescent sex offender literature, a
quantitative synthesis of the research comparing sex and non-sex
offenders can lay a valuable foundation for theoretical and applied
advances regarding adolescent sexual offending. Garber and Hollon
(1991) have nicely explained the logic of specificity designs in psychopathology research, which involve comparisons between clinical
groups of interest, such as comparisons of persons with schizophrenia
with persons who have other psychotic disorders, or in this context,
adolescent sex offenders and other adolescent offenders.
Specificity-design studies allow researchers to determine
whether a variable distinguishes adolescent sex offenders and is
therefore a potential causal candidate. Variables that distinguish
adolescent sex offenders from other adolescent offenders could
MALE ADOLESCENT SEXUAL OFFENDING
then be pursued in longitudinal research (to determine whether
they predict the onset of sexual offending rather than follow it) and
in experimental research (to determine whether randomized interventions that target these variables can reduce the likelihood of
onset or maintenance of sexual offending). Factors that do not
distinguish between the two groups cannot be sufficient causes of
adolescent sexual offending (although they still might play a more
complex causal role, for example, by interacting with another variable to increase the likelihood of sexual offending). Garber and
Hollon (1991) further distinguished between broad specificity, involving differences between a clinical group and a higher order category
(such as adolescent sex offenders and delinquents in general), and
narrow specificity, involving differences between clinical groups such
as comparisons of sex offenders with drug offenders.
Although we cannot fully test the multifactorial theories we
have briefly summarized here by examining specificity designs, a
meta-analysis of studies comparing adolescent sex offenders with
other adolescent offenders would be theoretically informative.
Theories that do not include factors distinguishing adolescent sex
offenders from other offenders would be incomplete, whereas
theories that include factors that do not distinguish between the
two groups would need to be reconsidered (by either dropping the
factor, or specifying interactions or other more complex causal
relationships). Below, we discuss special explanations of adolescent sexual offending that are particularly amenable to testing with
specificity designs.
In the present quantitative review, we focus on the validity of
special explanations of adolescent sexual offending that are testable by comparing adolescent sex offenders with other adolescent
offenders. This meta-analysis differs from a recent narrative review by van Wijk et al. (2006) by including a larger number of
studies, studies drawn from a longer period of time, and data on a
much larger set of variables; using quantitative estimates of the
magnitude of any group differences; and having greater statistical
power to detect group differences. We contrast offense-specific
theories with the more parsimonious view that sexual offending is
simply one of many manifestations of general antisocial tendencies
(which we also refer to as the “general delinquency explanation”)
and therefore can be explained with the same risk factors and
processes that have been successfully used in research on juvenile
delinquency (Loeber & Farrington, 1998; Quinsey, Skilling,
Lalumière, & Craig, 2004; Rutter, Giller, & Hagell, 1997). General
antisocial tendencies (or general delinquency risk factors) include
personality traits such as impulsivity and sensation seeking, procriminal attitudes and beliefs (e.g., “victims of crime get what they
deserve”), and associations with delinquent peers. All of these factors
predict delinquent behavior and are prominent in developmental models of juvenile delinquency in psychology and criminology. Besides
parsimony, there are empirical reasons to believe that the general
delinquency explanation has promise; for instance, criminologists
have consistently found that offenders rarely specialize in a particular
type of crime, and offense-specific models have typically had little
empirical success (Gottfredson & Hirschi, 1990).
In the following sections, we discuss the links between adolescent sexual offending and general delinquency, review the evidence in support of the general delinquency explanation of adolescent sexual offending, and summarize special explanations of
adolescent sexual offending. We then identify predictions that can
be derived from general and special explanations of adolescent
529
sexual offending and present the results of a meta-analysis of 59
independent studies that compared adolescent sex offenders with
adolescent non-sex offenders and thereby allowed us to test these
predictions and to test predictions derived from the theories of
sexual offending we reviewed earlier. We conclude by outlining a
model of adolescent sexual offending that is informed by the
results of this meta-analysis and that offers consilience with recent
developments in psychology and criminology and by discussing
the implications of our findings for the assessment, treatment, and
prevention of adolescent sexual offending.
The General Delinquency Explanation
Adolescent sexual offending could be parsimoniously explained as
a manifestation of general antisocial tendencies. First, a majority of
adolescent sex offenders have also committed nonsexual offenses (see
France & Hudson, 1993), so specialization in adolescent sexual offending is uncommon. Second, adolescent sex offenders who later
commit another crime are more likely to engage in a nonsexual crime,
such as theft, than another sexual crime (Caldwell, 2002; Worling &
Långström, 2006). Third, analyses of the criminal trajectories of
adolescent offenders suggest that sexual crimes tend to be committed
after an escalating history of nonsexual offenses (Elliott, 1994). Finally, variables associated with risk for general delinquency (such as
antisocial personality traits, pro-criminal attitudes and beliefs, associations with delinquent peers) are associated with both sexual and
nonsexual recidivism among adolescent sex offenders (Caldwell,
2002; Lipsey & Derzon, 1998; Prentky, Pimental, & Cavanaugh,
2006; Worling & Curwen, 2000).
From these different lines of empirical research, one might
expect that adolescent sex and non-sex offenders would score
similarly on measures of general delinquency risk factors—past
nonsexual criminal behavior, early conduct problems, antisocial
personality traits, antisocial attitudes and beliefs, association with
delinquent peers, and substance abuse— because these two groups
are essentially drawn from the same population of adolescent
offenders. One could even propose that adolescent sex offenders
should score higher, as a group, than other adolescent offenders on
these measures, because sexual offenses are serious violations of
social norms when compared with many nonsexual crimes, such as
theft or possession of illegal drugs, and sexual offending is often
observed at the end of an increasingly serious sequence of nonsexual offenses.
Special Explanations of Adolescent Sexual Offending
Influenced by the theories we have mentioned, special explanations for adolescent sexual offending have focused on such factors
as sexual abuse history, poor childhood attachment, heterosocial
incompetence, atypical sexual experiences, and atypical sexual
interests. In comparison, a general delinquency explanation would
focus on such variables as antisocial personality traits, early conduct problems, antisocial attitudes and beliefs, parental discipline,
supervision, and monitoring, interactions with delinquent peers,
and substance abuse, all of which have been found to distinguish
delinquents from nondelinquents in criminological and psychological research (reviewed in Quinsey et al., 2004; Rutter et al., 1997).
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SETO AND LALUMIÈRE
The Sexually Abused Sexual Abuser
The most frequently discussed special factor in explanations of
adolescent and adult sexual offending is sexual abuse history2
(Johnson & Knight, 2000; Knight & Sims-Knight, 2003; Kobayashi, Sales, Becker, Figueredo, & Kaplan, 1995; Marshall &
Barbaree, 1990). The sexually abused sexual abuser hypothesis
suggests that (male) children who are sexually abused are more
likely to engage in sexual offending later in life. Burton (2003)
described plausible mechanisms linking sexual abuse and later
sexual offending, including modeling of the perpetrator, conditioning as a result of pairing any sexual stimulation caused by the
sexual abuse with cues such as the type of acts that occurred, and
adopting permissive attitudes and beliefs about adult– child sex.
Consistent with the idea that modeling or another learning process
might explain the link between experiencing sexual abuse and later
sexual offending, Burton found that adolescent sex offenders who
had been sexually abused tended to perpetrate the same kinds of
sexual acts they had experienced themselves.
Thus, sexually abused sexual abuser explanations would predict
a specific association between sexual abuse and sexual offending
such that adolescent sex offenders are more likely to have experienced sexual abuse than adolescent non-sex offenders. Adolescent sex offenders may also be more likely to have experienced
(nonsexual) physical abuse or other forms of maltreatment, because different forms of abuse often co-occur, but one would
expect larger group differences in sexual abuse specifically. In
fact, physical abuse, neglect, and exposure to violence are related
to general delinquency (Kitzmann, Gaylord, Holt, & Kenny, 2003;
Maxfield & Widom, 1996). If a modeling process is involved in
the link between sexual abuse and sexual offending, then we would
also expect adolescent sex offenders to score higher than non-sex
offenders on variables reflecting exposure to sexual violence, but
not (or not as much) for variables reflecting exposure to nonsexual
forms of violence.
Poor Childhood Attachment
A great deal of attention has been paid to childhood attachment
in the literature on adolescent sexual offending (Marshall & Barbaree, 1990; Marshall, Hudson, & Hodkinson, 1993; Righthand &
Welch, 2001; Ryan, 1999; Smallbone, 2006). Marshall and Marshall (2000) have suggested that poor childhood attachment increases the risk of childhood sexual abuse because vulnerable boys
are more likely to seek relationships with adults other than their
parents. Insecure attachment is also thought, by these authors, to
increase the likelihood of sexual offending because poorly attached individuals are more likely to try to fulfill their intimacy
needs in inappropriate relationships. Indeed, recent studies have
reported that adult sex offenders differ from other offenders in
being more likely to have insecure childhood and adult attachment
styles (Lyn & Burton, 2004; Marsa et al., 2004). Smallbone
suggested that insecure attachment can increase the likelihood of
sexual offending by reducing empathic capacity, increasing emotional dysregulation, and increasing the likelihood of a coercive
interpersonal style (see also Baker, Beech, & Tyson, 2006).
Explanations that focus on poor childhood attachment would
predict adolescent sex offenders to score differently from adolescent non-sex offenders on measures of childhood attachment and
other aspects of the parent– child relationship, such as communication and satisfaction. However, there is no expectation that
adolescent sex offenders would differ on other aspects of family
functioning or family variables that are associated with general
delinquency, such as whether the youth lived with both biological
parents, familial substance abuse, or familial criminal history
(Amato & Keith, 1991; Loeber & Farrington, 1998).
Social Incompetence
Explanations that focus on social incompetence suggest that
adolescent sex offenders seek sexual contact with much younger
children or that they sexually coerce peers or adults because they
do not have the social skills to fulfill their sexual and emotional
needs in age-appropriate and consensual relationships (Finkelhor,
1984; Marshall & Barbaree, 1990; Ward & Siegert, 2002). In other
words, a social incompetence explanation proposes that adolescent
sex offenders have difficulty initiating or maintaining ageappropriate and consensual relationships because they have deficits in such skills as approaching someone, engaging them in
conversations, and accurately decoding affective cues during interactions with similar-aged peers (Becker & Kaplan, 1988; Knight
& Prentky, 1993; Marshall et al., 1993; Marshall, Serran, &
Cortoni, 2000; Worling, 2001). Consistent with this hypothesis,
Dreznick (2003) reviewed 14 studies (13 involving adult male
offenders) and found that sex offenders scored significantly lower
on both self-report and performance measures of heterosocial
skills (social skills in interactions with opposite-sex peers; Sell,
Wells, & Wypij, 1995) than did non-sex offenders. The sole study
of adolescent offenders found a similar group difference (Katz,
1990).
Social incompetence explanations predict that adolescent sex
offenders would score significantly lower than adolescent non-sex
offenders on measures of heterosocial skills. Adolescent sex offenders might also score lower than non-sex offenders on more
general measures of social skills and other social problems, but the
size of the group difference would be expected to be larger for
heterosocial skills in particular.
Sexual Development
Some explanations suggest that adolescent sex offenders differ
from other adolescents in aspects of their sexual development
(Knight & Sims-Knight, 2003; Malamuth et al., 1991; Marshall &
Barbaree, 1990). For example, Marshall and Marshall (2000) suggested that sexually abused individuals are different from nonabused individuals in having an earlier onset of masturbation and
2
Sexual abuse is not a good scientific term because it is generally not
behaviorally defined, and it often implies both harm to the child and the intent
to exploit or harm on the part of the older person, without assessing either harm
to the child or the older person’s intent. The one common element across
different operationalizations of sexual abuse is that there is sexual contact
between a child and a distinctly older youth or adult. However, this phrase is
cumbersome to use. We use the term sexual abuse because it is widely used in
scientific and nonscientific writings and because many of the studies in this
meta-analysis that examined sexual contact between a child and an older youth
or adult used items that refer to sexual abuse. Similarly, we use the term
physical abuse in this article.
MALE ADOLESCENT SEXUAL OFFENDING
greater use of sex as a means of coping with stress and other
problems. A related idea is that adolescent sex offenders experience earlier and more frequent exposure to sex, either by observing
others engaged in sexual activity or viewing pornography (Beauregard, Lussier, & Proulx, 2004; see Seto, Maric, & Barbaree,
2001).
At the same time, adolescent sex offenders would be expected to
be less successful in forming conventional sexual relationships, to
the extent that they have heterosocial skills deficits, as discussed in
the previous section. Integrating these hypotheses, one would
predict adolescent sex offenders, in comparison with adolescent
non-sex offenders, to have had earlier and more frequent exposure
to sex, either directly or through exposure to pornography, an
earlier onset of masturbation, and greater use of sex as a means of
coping. However, one would also expect adolescent sex offenders
to have had a later onset of sexual activities with consenting and
age-appropriate partners and fewer consenting and age-appropriate
sexual partners compared with other delinquents.
Atypical Sexual Interests
Explanations that focus on atypical sexual interest suggest that
some adolescent sex offenders differ from other adolescents in
their sexual interests in children or in coercive sex with peers or
adults and that these atypical sexual interests motivate their sexual
offenses (Becker & Kaplan, 1988; Finkelhor, 1984; Hall & Hirschman, 1991, Hall & Hirschman, 1992; Marshall & Barbaree, 1990;
Seto, Murphy, Page, & Ennis, 2003; Ward & Siegert, 2002). The
expectation of a group difference has been confirmed in laboratory
studies of adults that consistently have found sex offenders to
differ from other men in their relative sexual arousal to depictions
of children or coercive sex (e.g., Lalumière, Quinsey, Harris, Rice,
& Trautrimas, 2003; Rice & Harris, 2002), and measures of
atypical sexual interests are significant predictors of sexual recidivism by adult sex offenders (Hanson & Morton-Bourgon, 2005;
Seto, Harris, Rice, & Barbaree, 2004).
Two studies have shown that adolescent sex offenders, as a
group, show relatively more sexual arousal to stimuli depicting
children or coercive sex than do young adult comparison groups
(Robinson, Rouleau, & Madrigano, 1997; Seto, Lalumière, &
Blanchard, 2000), and two studies reported that arousal to stimuli
depicting children predicted sexual recidivism among adolescent
sex offenders (Clift, Rajlic, & Gretton, 2009; Rice & Harris, 2009).
Seto et al. (2003) found that sexual arousal to stimuli depicting
children was correlated with child victim characteristics among
adolescent sex offenders in a similar fashion as among adult sex
offenders (Seto & Lalumière, 2001). Worling and Curwen (2000)
found that self-reported sexual interest in children was associated
with sexual recidivism among adolescent sex offenders. Integrating these findings, we would predict adolescent sex offenders to
score higher on measures of atypical sexual interests than adolescent non-sex offenders.
Psychopathology
Different theorists have speculated that affective dysregulation
and personality problems can help explain sexual offending (Hall
& Hirschman, 1991, 1992; Ward & Siegert, 2002). Indeed, studies
have often found high levels of psychopathology—such as anxiety,
531
depression, and personality problems–in clinical or correctional
samples of adolescent and adult sex offenders (Galli et al., 1999;
Kafka & Hennen, 2002). Kafka (1997) suggested that the association of psychopathology and sexual offending reflects an underlying disturbance in serotonergic brain systems, because serotonin
levels are associated with mood, sexual behavior, and aggression.
Treatment with selective serotonin reuptake inhibitors can reduce
sex drive, and some clinical investigators have suggested that
treatment with such medications might even selectively reduce
paraphilic sexual arousal (Fedoroff, 1993; Greenberg & Bradford,
1997; Kafka, 1997). If these special explanations involving psychopathology are correct, then we would expect adolescent sex
offenders to score higher than adolescent non-sex offenders on
measures of mood and personality problems.
Cognitive Abilities
Cognitive limitations have been associated with sexual offending. Cantor, Blanchard, Robichaud, and Christensen (2005) conducted a meta-analysis of studies that compared male sex offenders with other males on measures of intelligence. Approximately
30% of the studies were of adolescent sex offenders. Adult sex
offenders scored significantly lower on measures of intelligence
than did other adult offenders, who, in turn, scored lower than
nonoffending controls. There was no significant difference between adolescent sex offenders and other adolescent offenders,
however, although the trend was for the sex offenders to have a
lower mean intelligence score. Cantor et al. (2004) found a similar
pattern of results for more specific measures of verbal and visuospatial learning and memory. Persons with lower cognitive abilities may have poorer judgment or impulse control and thus may be
more likely to commit sexual offenses opportunistically. Alternatively, persons with lower cognitive abilities may be more likely to
be sexually rejected by peers and thus may be more likely to turn
to children or to engage in sexual coercion against peers or adults.
One limitation of the Cantor et al. (2005) meta-analysis is that
it compared all available samples of sex offenders with all available samples of non-sex offenders. The samples of sex offenders
and of non-sex offenders may have differed in ways that affected
the intelligence scores that were obtained. In a direct comparison,
one could predict that adolescent sex offenders would score significantly lower than other adolescent offenders on measures of
cognitive abilities, including measures of intelligence, learning
difficulties, and academic achievement.
The Importance of Victim Age
Sexual victim age might moderate any differences between sex
offenders and non-sex offenders on the theoretically derived variables examined in this meta-analysis. Adult sex offenders who
target other (usually female) adults tend to be similar to non-sex
offenders on measures of general delinquency risk factors and are
more antisocial than adult sex offenders who target children (reviewed by Lalumière et al., 2005; Seto, 2008). One could assume
a similar pattern of results among adolescent sex offenders when
they are distinguished according to victim age: Adolescent sex
offenders with peer or adult victims might be similar to other
adolescent offenders on measures of general delinquency risk
factors, whereas adolescent sex offenders with child victims might
SETO AND LALUMIÈRE
532
score lower on these measures. Thus, the magnitude of any difference in general antisocial tendencies found between an undifferentiated group of adolescent sex offenders and a group of
non-sex offenders would depend on the proportion of the adolescent sex offender group who had victimized children.
Sexual victim age might also be an important moderator for
some special explanations of adolescent sexual offending. For
example, the mechanisms proposed by Burton (2003) and Marshall
and Marshall (2000) would suggest that the link between childhood sexual abuse and later sexual offending would be stronger for
adolescent sex offenders with child victims than for adolescents
who sexually offend against peers or adults, because the sexual
abuse and any resulting sexual fantasies would involve child cues.
As another example, Dreznick (2003) found that adult sex offenders with child victims scored significantly lower on measures of
heterosocial skills than adult sex offenders with adult victims.
Thus, we might expect that adolescent sex offenders with child
victims would score even lower on measures of heterosocial skills
than those who offended against peers or adults.
Overview of Hypotheses
A quantitative review of relevant studies using specificity designs to compare sex and non-sex offenders allows testing of
hypotheses derived from special and general explanations of adolescent sexual offending. Examining how adolescent sex offenders
compare with other adolescent offenders on theoretically derived
variables would suggest which factors need to be further considered in the difficult longitudinal and experimental work that is
needed to support causal inferences and, therefore, would contribute to the development of a comprehensive theory of adolescent
sexual offending that does not rely on extrapolation from the adult
offender literature.
Drawing from special explanations of adolescent sexual offending, we derived the following hypotheses:
Hypothesis 1. Adolescent sex offenders will be more likely to
have histories of childhood sexual abuse than will non-sex
offenders, and will also have greater exposure to sexual
violence, but they will not differ (or will differ less) with
regard to other forms of abuse, neglect, or exposure to nonsexual violence.
Hypothesis 2. Adolescent sex offenders will score higher than
non-sex offenders on variables reflecting poor childhood attachment but will not score higher (or will differ less) on
variables reflecting other aspects of family functioning, such
as familial substance abuse and familial criminality.
Hypothesis 3. Adolescent sex offenders will score higher than
non-sex offenders on variables reflecting heterosocial skills
deficits. They may also score higher on variables reflecting
general social skills deficits and other social problems such as
isolation, but the difference should be larger for social skills
involving interactions with opposite-sex peers.
Hypothesis 4. Adolescent sex offenders will score higher than
non-sex offenders on variables reflecting atypical sexual development, such as early exposure to sex or pornography, but
lower on variables representing conventional sexual experi-
ences, such as number of consenting and age-appropriate
sexual partners.
Hypothesis 5. Adolescent sex offenders will score higher than
non-sex offenders on variables reflecting atypical sexual interests (e.g., interest in sex with prepubertal children, interest
in coercive sex).
Hypothesis 6. Adolescent sex offenders will score higher than
non-sex offenders on measures of psychopathology, especially measures of mood problems or personality problems
other than antisocial personality traits.
Hypothesis 7. Adolescent sex offenders will score lower than
non-sex offenders on measures of cognitive abilities.
We also examined group differences with regard to impression
management, to determine whether the comparisons of study variables based on self-report could be explained by socially desirable
responding.
In contrast, a general delinquency explanation of adolescent sexual
offending predicts that adolescent sex offenders and non-sex offenders would be similar on general delinquency risk factors. In particular,
the general delinquency theory predicts that the two groups will show
a similar (and high) amount of past criminal behavior, conduct problems, antisocial personality traits, antisocial attitudes and beliefs,
association with delinquent peers, and substance abuse. According to
this explanation, there should be no difference between the two
groups on factors postulated by special explanations. Although this
prediction may appear to be a Sisyphean attempt to prove the null
hypothesis, because the general delinquency explanation proposes no
differences between adolescent sex offenders and non-sex offenders,
the use of meta-analysis helps to minimize problems associated with
the relatively low statistical power of individual studies and the
concomitant risk of Type II error. Demonstrating no significant difference between adolescent sex and non-sex offenders with a cumulatively large sample size and no significant heterogeneity of effect
sizes would support the general delinquency explanation.
Special and general explanations of adolescent sexual offending
are not mutually exclusive: It is possible that both special and
general factors are relevant such that adolescent sex offenders are
similar to adolescent non-sex offenders on antisocial tendencies
but significantly different on other theoretically derived variables
(see Lussier, 2005). In this situation, a pattern of significant group
differences in our meta-analysis would suggest the relative contributions of special and general factors in explaining adolescent
sexual offending. Finally, we expected that sexual victim age
would be a significant moderator of group differences, because of
the importance of sexual victim age among adult sex offenders and
recent evidence about the relevance of sexual victim age in adolescent sexual offending.
Method
Selection of Studies
We conducted searches of multiple electronic databases (Applied Social Sciences Index and Abstracts, Criminal Justice Abstracts, Criminology: A Sage Full-Text Collection, CSA Social
MALE ADOLESCENT SEXUAL OFFENDING
Services Abstracts, ERIC, Expanded Academic ASAP, International Bibliography of the Social Sciences, MEDLINE, National
Criminal Justice Reference Service, ProQuest Digital Dissertations, PsycINFO, Social Sciences Abstracts at Scholars Portal,
Social Science Citation Index, Sociology: A Sage Full-Text Collection, and Violence and Abuse Abstracts) to identify potential
specificity design studies, on the basis of their titles and abstracts,
using variations of the following search terms: “adolescent sex
offenders,” “juvenile sex offenders,” “adolescent sexual offending,” and “juvenile sexual offending.” We also reviewed the reference lists of relevant studies, review articles, and book chapters,
along with the electronic conference abstracts that were available
from the 2000 to 2005 annual meetings of the Association for the
Treatment of Sexual Abusers, a large international organization of
practitioners and researchers in the sex offender field. We contacted the first authors of studies that were included in the metaanalysis, or senior authors or faculty advisors when first authors
were unavailable, and asked them whether they had any unpublished manuscripts containing data from comparisons of adolescent sex and non-sex offenders. Finally, we contacted active investigators in the field of adolescent sexual offending and asked
them whether they had any unpublished manuscripts that would be
suitable for this meta-analysis.
We selected English-language studies presented, published, or
indexed (in the case of unpublished theses and dissertations) from
1975 to 2008. We excluded studies reported before 1975 because
these studies included sex offenders who would no longer be
considered as such under contemporary laws. For example,
Atcheson and Williams (1954) and R. Roberts, McBee, and Bettis
(1969) included a substantial number of youths designated as
“sexual delinquents” because of their promiscuity or homosexual
behavior. Contemporary sexual offender laws typically define
sexual offenses in terms of sexual behavior directed toward someone who does not consent to the behavior (in the case of sexual
coercion of peers or adults) or who is not legally able to provide
consent (in the case of sexual acts involving children or youths
below a legally defined age of consent). Few studies of adolescent
sex offenders were reported before 1975 (see review by Barbaree,
Hudson, & Seto, 1993).
Studies had to include at least one group of male adolescents
who had committed a documented sexual offense and at least one
comparison group of male adolescents who had committed a
documented nonsexual offense. In most cases, offenses were documented by a criminal charge, as most of the adolescents in the
study samples had been charged for their crimes. For example,
Napolitano (1996) was excluded because the adolescent sex offenders had a documented sexual offense, whereas the comparison
group did not necessarily have a documented nonsexual offense
(although all of the comparison participants met diagnostic criteria
for conduct disorder, indicating that they had engaged in antisocial
behaviors, many of which could have resulted in criminal charges,
e.g., drug use, theft, assaults). We did not include data from groups
of “status” offenders, that is, adolescents who were in trouble for
behaviors such as truancy or running away that would be legal if
they were older (e.g., Ford & Linney, 1995); some studies, however, included some status offenders among their non-sex offenders (e.g., Lincoln, 1993).
In 11 of the studies we included, some adolescents had not been
charged but had been placed in residential or treatment settings
533
because of sexual offenses they admitted or that were documented
in clinical files and were combined with other adolescents who had
been charged. All of the studies included adolescents who had
been charged: Davis-Rosanbalm (2003) and Dunning (1991) also
included adolescents who self-reported crimes; Epps (2000),
Miller (1997), and L. C. Roberts (1997) included adolescents with
documented offenses, for example, from child protection agency
records; and Frazier (1999), Miner (2003), Ness (2001), and Zakireh (2000; Zakireh, Ronis, & Knight, 2008) included adolescents
who were in treatment because of their sexual offending. Veneziano, Veneziano, LeGrand, and Richards (2004) indicated that
participants were either court-ordered or referred to residential
treatment. Racey, Lopez, and Schneider (2000) indicated only that
a majority of the adolescents in their sample had been charged.
Sex offenders could have been adjudicated for a nonsexual
offense, but non-sex offenders did not have any adjudicated sexual
offenses. Some adolescents assigned to the non-sex offender
group, however, may have committed officially undetected sexual
offenses. Fleming, Jory, and Burton (2002) and Spaccarelli, Bowden, Coatsworth, and Kim (1997) found that 20% and 14%,
respectively, of their adjudicated non-sex offenders admitted having committed sexual offenses. We retained these studies in the
meta-analysis because many other studies were also likely to
include data from non-sex offenders who had committed officially
undetected sexual offenses. Excluding these two studies while
retaining the others would introduce a study selection bias, as the
majority of other studies classified non-sex offenders on the basis
of their criminal records only; only seven studies explicitly indicated that they excluded non-sex offenders who self-reported committing sexual crimes. Van Wijk and his colleagues assigned
adolescent offenders according to their index or referral offense, so
non-sex offenders with a prior criminal history might have committed sexual offenses in the past (van Wijk, Blokland, Duits,
Vermeiren, & Harkink, 2007; van Wijk, Vreugdenhil, van Horn,
Vermeiren, & Doreleijers, 2007). As we note in the Discussion, the
inclusion of some adolescents with sexual offense histories in the
non-sex offender groups would attenuate any group differences
found in this meta-analysis.
Studies included adolescents who committed sexual offenses
involving physical contact with a victim, but at least eight of the
studies we examined in this meta-analysis also included some
adolescents who had committed noncontact sexual offenses, such
as indecent exposure: Csercsevits (2000), Gregory (1998), and
Spaccarelli et al. (1997) indicated only that they included noncontact offenders; Krauth (1998) indicated that 7% of her sample had
committed exhibitionistic offenses; two of the 17 adolescent sex
offenders in the sample originally reported by Lewis, Shanok, and
Pincus (1979; 1981) had committed exhibitionistic offenses; Milloy (1994, 1996) indicated that 9% of her sample had committed
noncontact offenses; and Zakireh (2000; Zakireh et al., 2008)
indicated that 2% of his sample had committed voyeuristic offenses. van Wijk, Blokland, et al. (2007) indicated that 18.8% of
their sample had committed nonviolent sexual offenses such as
indecency or exhibitionism, but indecency could still involve sexual contact, so the proportion who engaged in noncontact sexual
offenses was not clear. We did not find any studies that exclusively
recruited adolescents who committed sexual offenses that did not
directly involve contact with a victim.
534
SETO AND LALUMIÈRE
We limited studies to adolescents, defined here as persons ages
12 to 18 years, so studies of children or adults were not included.
Some studies included a few younger participants (e.g., ages 10
and 11 years in Krauth, 1998) and others included a few older
subjects (e.g., age 19 years in Zakireh, 2000), but most of the
participants in a given study were between the ages of 12 and 18
years. For example, the participants in L. C. Roberts (1997) ranged
from 13 to 20 years, but only three of the 35 sex offenders and one
of the 31 non-sex offenders was over the age of 18 years. We
excluded van Wijk, Loeber, et al. (2005) because some of the
participants were adults at the time they committed the offense that
placed them in the sex offender versus non-sex offender groups,
and study variables included information obtained during adulthood. We also focused on studies of males, because males commit
the large majority of sexual offenses, and there were too few
studies of female adolescent sex offenders for meta-analysis (Snyder & Sickmund, 2006). Osburn (2003) and Shields and Jordan
(1995) were excluded from the meta-analysis because some of the
non-sex offenders were female, whereas none or only one of the
sex offenders was female.
Both groups of adolescents had to be assessed in the same or an
equivalent correctional, mental health, or community setting (i.e.,
they had to have an equivalent point of entry into the original
study). Miner (2003) was included even though the two groups of
offenders were predominantly recruited from different settings,
because the residential treatment center from which the majority of
the sex offenders were recruited was comparable in security level
and availability of services to the training school from which the
majority of the non-sex offenders were recruited (Michael Miner,
personal communication, January 3, 2007). The study reported by
Yackovich (2002) was excluded from the meta-analysis because
all but one of the adolescent sex offenders was assessed in a
residential treatment program, whereas all of the adolescent nonsex offenders were recruited from a correctional facility. Franklin
(2000) was included in the meta-analysis, but only the data from
adolescent sex offenders and non-sex offenders assessed as inpatients were used; the data from sex offenders assessed as outpatients were excluded because there was no equivalent outpatient
group of adolescent non-sex offenders.
We selected studies that provided data for at least one variable
that could be assigned to one of the meta-analysis variable domains described below. Subgroups of sex offenders or non-sex
offenders, when present, were merged for the meta-analysis; for
example, violent and nonviolent non-sex offenders were combined
for the group comparisons. Studies that selected participants on the
basis of characteristics that were also variables in the metaanalysis were usually excluded. For examples, Blaske, Borduin,
Henggeler, and Mann (1989) selected sex and non-sex offenders
whose fathers were absent, Maring (1998) selected offenders who
met the diagnostic criteria for conduct disorder, and Thomas
(1986) excluded offenders who had ever committed a physical
assault. We retained studies that used selection or exclusion criteria that we considered to be necessary to conduct the study (e.g.,
a minimum intelligence score for studies involving the completion
of questionnaires, participants not being actively psychotic at the
time of the study assessment). Studies that matched adolescent
offender groups on age, socioeconomic status, ethnicity, or other
variables that were not analyzed in this meta-analysis were also
included.3
Studies had to provide sufficient information to calculate an
effect size, reported here as Cohen’s d. Our search led to the
inclusion of 59 independent studies representing a total of 3,855
adolescent sex offenders and 13,393 adolescent non-sex offenders.
These studies are summarized in Table 1 and are marked in the
Reference list with an asterisk. For studies that reported overlapping data sets, we selected the study that provided more data for
the meta-analysis: Awad and Saunders (1991) was selected over
Awad, Saunders, and Levene (1984) because the former reported
data on a larger sample. Fleming et al. (2002) was selected over
Burton, Miller, and Tai Shill (2002) because the former included
more variables. Lewis et al. (1979, 1981) and Rubinstein, Yeager,
Goodstein, and Lewis (1993) reported on different variables from
the same sample of sex and non-sex offenders, so all three are
included in the meta-analysis and recorded as one study. Rubinstein et al. (1993) reassigned two of the non-sex offenders to the
sex offender group upon discovery of additional information.
Daleiden et al. (1998) and Hilliker (1997) had almost entirely
overlapping samples but reported on different variables (Daniel
Hilliker, personal communication, January 17, 2006), so both are
included in the meta-analysis and recorded as one study. Similarly,
Zakireh (2000) and Zakireh et al. (2008) reported data from the
same sample but reported on different variables, so both are
included in the meta-analysis and recorded as one study.
The question of overlap could not be answered definitively for
several studies, which were therefore retained in the meta-analysis.
Jonson-Reid and Way (2001) reported on a large sample from 10
counties covered by the California Youth Authority, and Macri
(2000) also collected data from the California Youth Authority;
Capozza (1997) and Etherington (1993) reported data from California samples, and Katz (1990) appeared to have presented data
from a California sample. Miller (1997) and L. C. Roberts (1997)
collected their data around the same time from the same correctional facility in Illinois, and both completed their studies as part
of the dissertation requirement of the same graduate program.
Some studies were clearly conducted at the same sites but were
separated by the time period in which data were collected. Awad
and Saunders (1991) and Butler and Seto (2002) collected their
data from the same Toronto clinic, but from temporally nonoverlapping samples, whereas Jacobs, Kennedy, and Meyer (1997) and
Mattingly (2000) collected their data from the same Florida training school but at different times.
Selection of Variables
We examined the domains of age of first criminal justice contact, extent of criminal involvement, conduct problems, antisocial
tendencies, substance abuse, childhood abuse and exposure to
violence, family problems, interpersonal problems, sexuality, psychopathology, cognitive abilities, and impression management.
Results from the domains of age at first criminal justice contact,
extent of criminal involvement, and conduct problems have been
presented in a different form in a book chapter (Seto & Lalumière,
2006); we added five studies to these domains that we found after
the completion of the chapter (Chewning, 1991; Epps, 2000;
Gregory, 1998; van Wijk, Blokland, et al., 2007; van Wijk, Vreug3
Lists of excluded studies and variables are available from the authors.
MALE ADOLESCENT SEXUAL OFFENDING
535
Table 1
Summary of 59 Studies Included in Meta-Analysis
Study
Abbott (1991)
Aljazireh (1994)
Awad & Saunders (1991)
Barham (2001)
Benoit & Kennedy (1992)
Briley (2004)
Butler & Seto (2002)
Capozza (1997)
Caputo et al. (1999)
Chewning (1991)
Csercsevits (2000)
Daleiden et al. (1998); Hilliker (1997)
Davis-Rosanbalm (2003)
Dunning (1991)
Epps (2000)
Etherington (1993)
Fagan & Wexler (1988)
Fleming et al. (2002)
Flores (2003)
Ford & Linney (1995)
Franklin (2000)
Frazier (1999)
Gregory (1998)
Griggins (1989)
Hill (2000)
Hollin & Swaffer (1993)
Jacobs (1999); Jacobs et al. (1997)
Jonson-Reid & Way (2001)
Katz (1990)
Krauth (1998)
Krupica (1997)
Lee (1994)
Leguizamo (2000)
Lewis et al. (1979, 1981); Rubinstein
et al. (1993)
Lincoln (1993)
Lindsey et al. (2001)
Macri (2000)
Mattingly (2000)
Miller (1997)
Milloy (1994, 1996)
Miner (2003)
Ness (2001)
Oliver et al. (1993)
Racey et al. (2000)
Risk (1993)
L. C. Roberts (1997)
Sivley (1998)
Spaccarelli et al. (1997)
Tarter et al. (1983)
Tinklenberg et al. (1981)
Truscott (1993)
Valliant & Bergeron (1997)
Van Ness (1984)
van Wijk, Blokland, et al. (2007)
van Wijk, van Horn, et al. (2005)
van Wijk, Vreugdenhil, et al. (2007)
Veneziano et al. (2004)
Wong (2002)
Zakireh (2000); Zakireh et al. (2008)
Source for offender samples
Sample size
Probation, majority at mental health clinic
Residential treatment centers
Family court clinic
Residential treatment centers
Secure training school
Training school
Family court clinic
California Youth Authority
Detention facility
Probation offices
Detention center or treatment program
Correctional facilities in three states
Age range or
mean age (in years)
40 ASOs, 40 NSOs
54 ASOs, 16 NSOs
94 ASOs, 24 NSOs
42 ASOs, 32 NSOs
50 ASOs, 50 NSOs
51 ASOs, 19 NSOs
32 ASOs, 82 NSOs
57 ASOs, 54 NSOs
23 ASOs, 47 NSOs
20 ASOs, 20 NSOs, 20 NOs
69 ASOs, 71 NSOs
289 ASOs, 138 NSOs,
135 NOs
Secure detention facility
46 ASOs, 63 NSOs
Residential or outpatient treatment
55 ASOs, 53 NSOs
Various youth agencies
54 ASOs, 54 NSOs
Residential treatment center
20 ASOs, 20 NSOs, 20 NOs
One of five urban juvenile courts
34 ASOs, 208 NSOs
Training school, residential treatment center, or group home 161 ASOs, 196 NSOs
Juvenile detention facility or probation
30 ASOs, 34 NSOs
Evaluation center or long-term residential facility
35 ASOs, 26 NSOs
State training school
30 ASOs, 29 NSOs, 22 NOs
Detention center, training school, or treatment program
30 ASOs, 36 NSOs
Detention facilities
58 ASOs, 116 NSOs
On probation
26 ASOs, 26 NSOs
Detention centers
26 ASOs, 110 NSOs
Residential treatment center
7 ASOs, 11 NSOs
Training school
78 ASOs, 78 NSOs
California Youth Authority
304 ASOs, 5,778 NSOs
Residential treatment facilities
31 ASOs, 34 NSOs, 71 NOs
Texas juvenile corrections
218 ASOs, 200 NSOs
Correctional facility
40 ASOs, 40 NSOs
Youth service or family court system in Alabama
34 ASOs, 35 NSOs, 24 NOs
Secure training school
75 ASOs, 53 NSOs
13–17
13–18
13–17
13–18
Mean age ⫽ 16
Mean age ⫽ 17
11–17
12–18
13–17
12–19
12–17
12–18
13–17
15–20
13–18
11–18
Mean age ⫽ 15
10–17
14–18
12–18
13–20
Secure correctional school
Juvenile courts
Secure treatment facility
California Youth Authority
Training school
Residential youth center
Washington state juvenile corrections
Residential or correctional facility
Residential treatment center
Juvenile court assessment clinic
Mental health center, training school, or treatment program
Youth correctional facility
Juvenile detention center
Court-ordered treatment
Juvenile assessment unit
Court-referred psychiatric assessments
Secure detention center in California Youth Authority
Adolescent offender assessment unit
Juvenile custodial facility
Youth correctional facilities
Forensic psychiatric service
Forensic assessment service
Youth detention centers
Residential treatment facility
Custodial facility or community services
Inpatient or outpatient treatment facilities
Mean age ⫽
9–17
13–18
15–25
13–18
13–18
Mean age ⫽
13–17
12–18
Mean age ⫽
13–18
15–17
13–20
12–17
12–17
Mean age ⫽
12–21
12–18
16–18
14–19
Mean age ⫽
Mean age ⫽
12–18
12–17
Mean age ⫽
13–19
19 ASOs, 80 NSOs
30 ASOs, 28 NSOs, 27 NOs
27 ASOs, 54 NSOs, 74 NOs
62 ASOs, 64 NSOs
120 ASOs, 145 NSOs
50 ASOs, 50 NSOs
59 ASOs, 197 NSOs
38 ASOs, 38 NSOs
47 ASOs, 90 NSOs, 80 NOs
50 ASOs, 100 NSOs
36 ASOs, 38 NSOs
17 ASOs, 17 NSOs, 17 NOs
35 ASOs, 31 NSOs
31 ASOs, 34 NSOs
24 ASOs, 186 NSOs
14 ASOs, 59 NSOs
63 ASOs, 230 NSOs
23 ASOs, 130 NSOs
16 ASOs, 13 NSOs, 13 NOs
29 ASOs, 27 NSOs
712 ASOs, 4,768 NSOs
112 ASOs, 165 NSOs
30 ASOs, 368 NSOs
60 ASOs, 60 NSOs
50 ASOs, 25 NSOs
50 ASOs, 50 NSOs
12–17
12–18
Mean age ⫽ 14
14–17
12–18
13–20
12–16
15–20
13–18
12–18
12–18
16–20
15
16
15
16
17
15
16
Note. The maximum sample sizes listed here are reported in the original studies; because of missing data, smaller samples may have been used in the
calculations reported in the following tables. The mean age is reported when the age range of participants was not clearly specified. The total sample sizes
reported in this article (3,855 ASOs and 13,393 NSOs) refer to the number of participants with valid information for at least one study variable. ASOs ⫽
adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; NOs ⫽ nonoffenders.
536
SETO AND LALUMIÈRE
denhil, et al., 2007) and excluded five other studies on the basis of
a reconsideration of our study selection criteria (Blaske et al.,
1989; Maring, 1998; Nagel, 1996; Shields & Jordan, 1995; Symboluk, Cummings, & Leschied, 2001).
Studies were double-coded and discrepancies in coding were
resolved by the two authors. Assignments to study domains were
made by consensus of the two authors. Some of these domains are
self-explanatory from their labels; the others are described below.
All variables having to do with one of these domains were included, with some exceptions. Variables reflecting conduct problems specifically in the sexual domain were excluded; this exclusion was not perfect because sexual items were embedded in some
composite measures (e.g., “total conduct problems” reported in
Butler & Seto, 2002, includes an item about forcing sex on
someone). Variables with asymmetric sources of information were
excluded; for example, Rubinstein et al. (1993) reported on sexual
abuse history, but this information was obtained from interview
and file information for the adolescent sex offenders and from
interview alone for the non-sex offenders. Variables that could not
be assigned to a study domain were excluded from the metaanalysis (e.g., Rorschach inkblot test scores; McCraw & PeggMcNab, 1989).
used a commercially available statistical program, Biostat’s Comprehensive Meta-Analysis, Version 1.0.25 (an update to Version 1;
2000), for the calculation of average d values, 95% confidence
intervals, and heterogeneity of d values, under a random-effects
model. A random-effects model was chosen over a fixed-effect
model because we expected that there might be multiple (true)
effect sizes as a result of factors that we could not examine in this
study; for instance, the size of the group difference might vary
depending on sample characteristics, such as the type of sex
offenders (intra- vs. extrafamilial offenders) or of non-sex offenders (adolescence-limited offenders vs. life-course-persistent offenders). A random-effects model produces wider confidence intervals than does a fixed-effect model and thus is more
conservative (Borenstein, Hedges, Higgins, & Rothstein, 2009).
The two groups were considered to be different in a given
variable category when the 95% confidence intervals around the
average d value did not include zero. We examined victim age
(discussed earlier) and source of information (see next section) as
potential moderator variables when the heterogeneity statistic (Q)
was statistically significant at p ⬍ .05, a sufficient number of
studies for such an analysis existed, and there was a rationale from
previous research for examining victim age or information source
as moderators.
Effect Size
We used Cohen’s d as the index of effect size. Cohen’s d represents
the standardized mean difference between groups of adolescent sex
offenders and adolescent non-sex offenders [(Maso – Mnso) / SDpooled].
A d value of ⫹.50, for example, indicates that adolescent sex offenders scored one half standard deviation greater than non-sex offenders
on that variable. Because d is rarely reported in studies, we calculated
it from group means and standard deviations when these were available; otherwise, we calculated d from t-test values.
For comparisons reported as percentages (e.g., proportion of
offenders with prior offense histories) or frequencies, we calculated chi-square statistics, corrected for continuity, which could
then be transformed into a d value. We did not include variables
with insufficient information to calculate d, such as statements
about the presence or absence of a statistically significant difference without any accompanying statistics. Thus, Kempton and
Forehand (1992) was excluded from the analysis because none of
the variables they reported had sufficient information for our
analysis.
Analytical Strategy
We examined different variable categories in many of the domains. For example, the domain of antisocial tendencies contains
the variable categories of antisocial personality traits, antisocial
attitudes and beliefs, and antisocial associations. Each study could
contribute only one effect size per variable category. When a study
reported more than one variable for a given category, an average
weighted effect size was calculated for these variables and used in
the meta-analysis. Sample size sometimes varied from variable to
variable within a study.
All effect sizes were independent within a category. Individual
studies could contribute effect sizes to more than one variable
category, within or across domains. Study effect sizes were
weighted by the study inverse variance for the main analyses. We
Source of Information
A salient methodological issue in adolescent offender research
is the validity of self-report. For example, adolescent sex offenders
may report a more extensive history of sexual abuse because the
intuitive association between childhood sexual abuse and later
sexual offending may help justify their behavior or because being
identified as a victim of sexual abuse might elicit sympathetic
treatment. At the same time, adolescent non-sex offenders may be
more reluctant to report a history of sexual abuse because of
greater embarrassment or shame in talking about their sexual
experiences. Moreover, the imperfections of human memory are
well documented, and longitudinal research shows significant differences can exist between adult memories of early adolescence
and what was actually reported by the participants at the time
(Offer, Kaiz, Howard, & Bennett, 2000; Widom & Morris, 1997;
Widom & Shepard, 1996). To examine this issue, we distinguished, when possible, between variables based on self-report and
variables based on information obtained from other sources (parents, teachers, or clinicians; clinical or institutional files; or police,
court, or correctional records). We also compared the two groups
of adolescent offenders on variables in the domain of impression
management to determine whether differences might be attributable in part to socially desirable responding.
Publication Bias
We included both published and unpublished studies in this
meta-analysis. Sources of studies included peer-reviewed journal articles, theses and dissertations, government reports, and
conference presentations; some of the data reported by Lewis
and colleagues came from a book chapter (Lewis et al., 1981),
but other data from these authors came from two peer-reviewed
articles (Lewis et al., 1979; Rubinstein et al., 1993). We considered studies appearing in peer-reviewed journal articles to be
MALE ADOLESCENT SEXUAL OFFENDING
published (k ⫽ 27); all other sources were considered to be
unpublished (k ⫽ 32). We examined whether publication status
affected the size of the group differences in most of the variable
domains.
Results
Overview
The main results are reported in Tables 2 through 12. Each table
shows the effect size for each variable or group of variables, listed
by study, along with the sample size and the group mean or
percentage values for each variable. The lines in boldface indicate
the meta-analytic calculations, including number of studies (k),
overall sample size, average d, the 95% confidence interval for d,
and the Q statistic of heterogeneity among the d values. The main
results for tests of the general and special explanations of adolescent sexual offending are summarized in Figures 1 through 7.
Following Cohen (1992), we considered effect sizes of 0.20 as
small, 0.50 as medium, and 0.80 as large. As a basis of comparison
for the effect sizes obtained in this meta-analysis, Moffitt and
Caspi (2001) compared 47 adolescent male life-course persistent
offenders with a large cohort of adolescents and obtained effect
sizes of approximately 0.20 for parental convictions, 0.50 for
inconsistent discipline, 0.75 for mother’s mental health problems,
and 1.00 for peer rejection.
We began by determining whether a general delinquency
explanation was sufficient to account for adolescent sexual
offending. We first examined domains pertaining to general
delinquency risk factors (age of first criminal justice contact,
extent of criminal involvement, conduct problems, antisocial
tendencies, and substance abuse) and then examined domains
relevant to special explanations of adolescent sexual offending:
childhood abuse and exposure to violence, family problems,
interpersonal problems, sexuality, psychopathology, and cognitive abilities. Finally, we examined the additional domain of
impression management.
537
Age at First Criminal Justice Contact
Nine studies contributed to the domain of age at first criminal
justice contact (Table 2). Age at first contact was early for both
groups. Adolescent sex offenders were slightly older than nonsex offenders at age of first contact with the criminal justice
system, but this difference was small and not statistically significant. There was no significant group difference when we
examined the six studies that reported age at first contact from
official records (police, court, or correctional records). Effect
sizes were heterogeneous for both the overall and official
record comparisons, suggesting the presence of additional moderator variables.
Extent of Criminal Involvement
Seventeen studies contributed to this domain (Table 3). Both
groups had extensive criminal histories when compared with a
representative American sample of adolescents: Snyder and Sickmund (1999) reported that 9% to 12% of male youths between the
ages of 12 and 16 years had ever been arrested, whereas 4% to 7%
had been arrested two or more times. Every one of the 17 studies
reported that adolescent sex offenders had a less extensive criminal
history than did non-sex offenders. This consistent finding was
obtained despite the fact that non-sex offenders were constrained
in their offense history; by definition, non-sex offenders could not
have any adjudicated sexual offenses, whereas sex offenders could
have charges for both sexual and nonsexual offenses. Five of the
17 studies specifically examined only nonsexual offense histories
(Flores, 2003; Hilliker, 1997; Ness, 2001; Sivley, 1998; Zakireh,
2000).
The average effect size for extent of criminal involvement was
statistically significant and medium in size. Similar results were
observed among the 11 studies that provided information on only
those offenses that occurred prior to the index offense and among
the six studies that provided information on prior offenses only and
relied on official records. The effect sizes were heterogeneous in
Figure 1. Antisocial tendencies. Number of effect sizes are indicated within parentheses. More positive effect
sizes indicate that adolescent sex offenders scored higher than adolescent non-sex offenders. Bars indicate 95%
confidence intervals.
SETO AND LALUMIÈRE
538
Table 2
Age at First Criminal Justice Contact (Nine Studies)
M or %
Study
Domain/variable
ASOs
N
NSOs
ASOs
NSOs
d
95% CI
Heterogeneity (Q)
K⫽9
Age at first
contact
907
6,795
0.11
ⴚ0.06 to ⴙ0.28
23.8, p ⬍ .005
K⫽6
Official records
only
559
6,565
0.12
ⴚ0.08 to ⴙ0.31
13.9, p ⬍ .05
Barham (2001)
Daleiden et al. (1998);
Hilliker (1997)
Flores (2003)
Gregory (1998)
Age first offense
13.2
13.3
42
32
⫺0.03
Age first arrest
Age first chargea
First
adjudication
ⱕ13a
Age first state
referrala,b
Incarcerated
before 15a
Age first
juvenile court
Age first
convictiona
Police arrest
⬍13a
12.7
13.6
43%
11.9
12.2
51%
289
30
58
138
34
116
0.33
0.72
0.12
12.7
12.0
78
78
0.33
9%
6%
304
5,778
⫺0.05
11.6
12.3
17
61
⫺0.37
13.4
13.4
59
197
0.00
47%
34%
30
361
⫺0.12
Jacobs (1999); Jacobs et
al. (1997)
Jonson-Reid & Way
(2000)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Milloy (1994, 1996)
Van Wijk, Vreugdenhil,
et al. (2007)
Note. ASOs ⫽ Adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; CI ⫽ confidence interval. Studies are scored such that a positive d
indicates that ASOs had an older age at first contact than did NSOs.
a
Information from official records. b First referral to state juvenile correctional authorities.
all of these comparisons, suggesting the presence of additional
moderator variables.
Conduct Problems
We defined conduct problems as disruptive, troublesome, or
rule-breaking behaviors that may not necessarily lead to involvement in the criminal justice system. Examples of conduct
problems include fighting, disruptive classroom behavior, and
truancy. Fifteen studies contributed to this domain (Table 4).
Both groups scored fairly high on conduct problems (e.g.,
above-average scores on the Youth Self Report when compared
with age-based norms); majorities of both groups had been
suspended or expelled from school in three of four studies, as
compared with 42% of a representative sample of adolescents
between the ages of 12 and 16 year who had ever been suspended from school (Snyder & Sickmund, 2006). Eleven of the
15 studies found that adolescent non-sex offenders had higher
scores in this domain. The overall group difference effect size
was negative, small, not statistically significant, and significantly heterogeneous.
Some conduct problem variables were based on the offenders’
self-report only, whereas other variables were based on reports
from others (e.g., parents, teachers, clinicians). We calculated, for
each study, an average effect size for all variables based on
self-report and an average effect size for all variables based on
other sources of information. Only three studies produced effect
sizes for both self-report and other sources of information (Butler
& Seto, 2002; Epps, 2000; Ford & Linney, 1995). Nine studies
included variables based solely on self-report; they produced a
small, nonsignificant, and positive average effect size. Nine studies
included variables that were based on sources other than selfreport. These studies produced a negative and significant mean
effect size, thus suggesting that adolescent sex offenders had fewer
conduct problems than adolescent non-sex offenders using sources
other than self-report. The heterogeneity statistics suggested that
other moderators were also present.
Antisocial Tendencies
We defined antisocial tendencies as personal characteristics
associated with a propensity to engage in antisocial or criminal
behavior, comprising personality traits, attitudes and beliefs,
and associations with delinquent peers. This domain can be
contrasted with the previous three domains, which contain
variables reflecting actual involvement in antisocial or criminal
behavior. The distinction is not perfect because some variables
in this domain include behavioral items; for example, the Psychopathy Checklist assesses personality traits such as impulsivity, grandiosity, and callousness but also contains items about
early behavioral problems and criminal involvement. Thirtyone studies contributed to this domain, which we divided into
three categories (Table 5). The source of information was
almost exclusively self-report.
The category of antisocial personality traits (k ⫽ 24) includes
such measures as the Psychopathic Deviate scale of the Minnesota
Multiphasic Personality Inventory (sources of the scales are reported in the original studies), subscales of the Jesness Inventory,
MALE ADOLESCENT SEXUAL OFFENDING
539
Table 3
Extent of Criminal Involvement (17 Studies)
M or %
Study
Domain/variable
ASOs
N
NSOs
ASOs
NSOs
d
95% CI
Heterogeneity (Q)
K ⫽ 17
Criminal history
1,772
9,483
ⴚ0.54
ⴚ0.68 to ⴚ0.40
71.6, p ⬍ .0001
K ⫽ 11
Prior criminal history only
1,124
8,913
ⴚ0.45
ⴚ0.61 to ⴚ0.29
38.8, p ⬍ .0001
K⫽6
Prior criminal history;
official records only
566
6,276
ⴚ0.51
ⴚ0.79 to ⴚ0.22
29.2, p ⬍ .0001
Abbott (1991)
Barham (2001)
Butler & Seto (2002)
Daleiden et al. (1998);
Hilliker (1997)
Epps (2000)
Flores (2003)
Ford & Linney (1995)
Gregory (1998)
Hill (2000)
Jacobs (1999); Jacobs
et al. (1997)
Jonson-Reid & Way
(2001)
Krauth (1998)
Milloy (1994, 1996)
Ness (2001)
Any prior history
No. prior offenses
No. prior chargesa
32%
1.5
2.8
75%
2.6
6.8
40
42
32
40
32
81
⫺0.88
⫺0.51
⫺1.02
No. charges
No. offenses and convictionsa
No. chargesa
Any prior offensesa
Ever prior adjudicationa
No. court referralsa
7.0
7.2
4.8
54%
59%
4.4
11.5
12.1
12.5
96%
64%
8.6
289
54
30
35
58
26
138
54
34
26
116
110
⫺0.49
⫺0.45
⫺1.35
⫺0.93
⫺0.08
⫺0.91
No. prior delinquent referralsa
12.1
17.0
78
78
⫺0.45
3⫹ prior petitionsa
No. juvenile referralsa
No. prior convictionsa
% with previous. . .b
Break and enter
Stolen property
Unlawful driving auto
Assault and battery
Retail fraud
Larceny
Destruction of property
Home invasion
Curfew violation
Parole/probation breach
Felonious assault
Incorrigibility
Weapons
Other criminal behavior
Other status offenses
Convicted any nonsexual
37%
1.6
3.9
58%
2.9
7.0
304
218
59
47
5,778
200
197
90
⫺0.18
⫺0.71
⫺0.61
⫺0.20
8%
0%
0%
8%
13%
8%
6%
4%
4%
4%
6%
8%
0%
26%
2%
26%
23%
9%
12%
22%
21%
16%
13%
13%
10%
9%
7%
4%
6%
49%
8%
59%
31
34
⫺0.63
Has criminal record
53%
78%
379
2,425
⫺0.40
1.7
1.9
50
50
⫺0.12
Sivley (1998)
Van Wijk, Blokland,
et al. (2007)
Zakireh (2000);
Zakireh et al.
(2008)
No. prior arrests
Note. ASOs ⫽ Adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; CI ⫽ confidence interval.
a
Information from official records. b Includes only crimes with a base rate of 5% or more for one of the two groups, in order to avoid diluting any real
group difference by including crimes with very low base rates.
and the Buss Durkee Hostility Inventory. Adolescent sex offenders
did not differ from non-sex offenders, and both groups tended to
have above-average scores relative to norms on standardized personality measures (Minnesota Multiphasic Inventory–Adolescent
Version, Millon Adolescent Personality Inventory, and modified
version of the Psychopathy Checklist—Revised). Only five studies
presented data based on sources other than self-report, again with
no significant group difference.
Adolescent sex offenders did not differ from non-sex offenders in the variable category of antisocial attitudes and beliefs
(k ⫽ 12). We could also distinguish between antisocial attitudes
and beliefs about sex, women, or sexual offending and other
kinds of antisocial attitudes and beliefs. Some theorists have
proposed that sex offenders are especially likely to endorse
antisocial attitudes and beliefs related to their sexual offending,
such as favorable attitudes about having sex with children,
negative attitudes about women, and acceptance of myths about
rape (Hall & Hirschman, 1991, 1992; Ward & Beech, 2005;
Ward, Hudson, Johnston, & Marshall, 1997). Thus, unlike the
other categories in this domain or the previous general delinquency domains, one could predict from special explanations
that adolescent sex offenders would score higher than non-sex
SETO AND LALUMIÈRE
540
Table 4
Conduct Problems (15 Studies)
M or %
Study
Domain/variable
K ⫽ 15
Conduct problems
K⫽9
Self-report only
K⫽9
Other sources of information
Awad & Saunders (1991)
Antisocial behavior
School behavioral problems
Kindergarten difficult
Total conduct problems
YSR externalizinga
YO-LSI education/employmentb
Fightinga
Shopliftinga
Running awaya
Stealinga
Lyinga
Setting firesa
Destroy thingsa
Ditched class (truancy)a
School suspensiona
Nonsexual violencea
No. school suspensions
No. school expulsions
Behavioral/emotional problems
Truancy
Delinquencya
YO-LSI education/employmenta
Violent behavior at school
K-SADS conduct disordera
MAPI attendancea
MAPI social conformitya
Other delinquencya
Ever suspended from school
Emotional problems in class
Fightinga
Cruelty to animalsa
Fire settinga
Stealinga
Expelled from school
Suspended last year
Physically aggressive
Cruel to animals
Weapon use
Arson
Theft
Truancy
Running away
Verbal threats
Assaults
Assaults (special security)
Used weapon in offense
Excessively aggressive
Previous escape from custody
Delinquency
Disciplinary school problems
Fire setting
Truancy
Running away
Disobedience, authority problems
Butler & Seto (2002)
Chewning (1991)
Davis-Rosanbalm (2002)
Epps (2000)
Etherington (1993)
Ford & Linney (1995)
Gregory (1998)
Krauth (1998)
Milloy (1994, 996)
Ness (2001)
N
ASOs NSOs ASOs NSOs
d
95% CI
1,311 4,816 ⴚ0.09 ⴚ0.27 to ⴙ0.09
66.2, p ⬍ .0001
0.08 ⴚ0.25 to ⴙ0.40
36.9, p ⬍ .0001
305
832
1,125 4,135 ⴚ0.28 ⴚ0.44 to ⴚ0.13
53%
67%
22%
9.4
55.5
3.2
35%
50%
15%
40%
55%
25%
35%
65%
35%
5.9
0.96
0.41
54%
37%
29.6
5.5
41%
63.1
57.4
67.5
28%
71%
26%
14%
11%
17%
14%
12%
54%
43%
4%
16%
13%
25%
25%
12%
41%
25%
9%
17%
25%
14%
64%
32%
13%
26%
11%
74%
88%
71%
25%
15.8
59.2
4.8
85%
80%
40%
55%
65%
25%
45%
80%
55%
4.1
0.97
0.48
72%
52%
37.4
5.9
44%
55.5
48.2
59.4
15%
88%
35%
19%
0%
4%
4%
16%
83%
73%
4%
48%
5%
68%
63%
32%
38%
28%
6%
19%
21%
21%
93%
46%
0%
46%
27%
97%
Heterogeneity (Q)
94
24 ⫺0.19
30
30
32
20
47 ⫺0.75
75
82
20 ⫺0.37
43
54
46
0.53
54 ⫺0.18
20
20
0.56
35
26
0.09
58
216
215
156
185
164
181
208
192
59
116 ⫺0.08
185 ⫺0.50
194
195
176
192
196
161
195
197 ⫺0.01
47
90 ⫺0.30
20.8, p ⬍ .01
MALE ADOLESCENT SEXUAL OFFENDING
541
Table 4 (continued)
M or %
Study
Spaccarelli et al. (1997)
Van Wijk, Blokland, et al. (2007)
Van Wijk, Vreugdenhil, et al. (2007)
Zakireh (2000); Zakireh et al. (2008)
Domain/variable
Serious violencea
Diagnosed conduct disorder
YSR externalizinga
MASA expressive aggressiona
N
ASOs NSOs ASOs NSOs
38%
18%
51.9
0.73
51%
36%
55.7
0.37
24
557
30
49
d
95% CI
Heterogeneity (Q)
186 ⫺0.14
3,377 ⫺0.26
358 ⫺0.32
47
0.87
Note. ASOs ⫽ Adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; CI ⫽ confidence interval; K-SADS ⫽ Schedule of Affective Disorders
and Schizophrenia for School-Aged Children; MAPI ⫽ Millon Adolescent Personality Inventory; MASA ⫽ Multidimensional Assessment of Sex and
Aggression; RBPC ⫽ Revised Behaviour Problem Checklist; YO-LSI ⫽ Young Offender Level of Supervision Inventory; YSR ⫽ Youth Self-Report. The
sources for these scales are reported in the original articles.
a
Based on self-report only. b Six of ten items pertain to school behavioral problems.
offenders on antisocial attitudes and beliefs about sex, women,
or sexual offending. This prediction was not supported: Adolescent sex offenders did not differ from non-sex offenders
across the nine studies that reported antisocial attitudes and
beliefs about sex, women, or sexual offending. Adolescent sex
offenders scored significantly lower than non-sex offenders on
antisocial attitudes and beliefs that were not related to sex,
women, or sexual offending.
Finally, adolescent sex offenders scored lower than non-sex
offenders in the category of antisocial associations for all but one
of the eight studies. We defined antisocial associations as interactions with delinquent peers or gang involvement. The group difference was of medium size and statistically significant. The group
difference appeared to be particularly large for studies that were
based on self-report.
Substance Abuse
There was much variability in the definition and prevalence of
substance use problems across the 20 studies contributing to this
domain (Table 6). Nevertheless, all but one study produced a
negative effect size, suggesting greater substance use problems
among non-sex offenders. The average effect sizes were small to
medium, and were heterogeneous for all comparisons. Source of
information did not have a significant impact on group differences,
and type of substances (alcohol vs. other drugs) did not seem to
matter either.
General Delinquency Risk Factors and Victim Age
The average effect sizes of the variable categories in the criminal history and antisocial tendencies domains are presented in
Figure 1. As shown, adolescent sex offenders were less antisocial
overall than were adolescent non-sex offenders. Most of the average effect sizes, however, were significantly heterogeneous, suggesting that one or more study or sample characteristic moderated
effect sizes. As noted, we had found that source of information was
a significant moderator for conduct problems and antisocial associations. In this section, we examined sexual victim age as a
moderator of group differences, collapsing across all variable
categories.
Fifteen studies included in the domains of age at first contact,
extent of criminal involvement, conduct problems, antisocial
tendencies, and substance abuse provided information about the
proportion of the adolescent sex offender sample who offended
against at least one child; the other sex offenders had peer or
adult victims only. For this analysis, we calculated, for each of
the 15 studies, an average weighted effect size for all antisocial
variables. Age at first contact was reverse coded so that a
younger age meant greater delinquency risk. We then correlated
these study-average effect sizes with the study proportions of
adolescent sex offenders who offended against children.4 The
proportions of offenders with child victims ranged from .38 to
1.0 across the 15 studies. The resulting correlation, statistically
controlling for study sample size, was r(12) ⫽ ⫺.07, p ⫽ .81.
We also examined the partial correlation when the proportion of
adolescent sex offenders with child victims and sample size
were log-transformed, to compensate for non-normal distributions on these variables, and obtained a similar result, r(12) ⫽
⫺.21, p ⫽ .47.
We next focused on the six studies that provided data that
allowed us to directly compare sex offenders against at least one
child and sex offenders against only peers or adults on at least
one antisocial variable (Awad & Saunders, 1991; Epps, 2000;
Ford & Linney, 1995; Krauth, 1998; van Wijk, Blokland, et al.,
4
In all but two of the studies we examined for this analysis, child
victims were defined as a minimum of three to five years younger than
the offender. Some studies included maximum victim ages, ranging
from 10 to 13 years; for example, Epps (2000) specified that all child
victims were age 10 or younger without specifying a minimum age
difference. Griggins (1990) did not specify the child victim criteria but
did report the specific victim ages; the oldest victim was 13, five years
younger than the 18-year-old offender (who also had committed an
offense against a 5-year-old victim). Lee’s (1994) study differed from
the other studies by defining child victims as either four years younger
than the offender or 10 years old or younger. Chewning (1991) did not
specify the age criteria, noting only that all of the adolescent sex
offenders had committed “child molestation” offenses and had not
committed rape or sexual assault offenses. van Wijk, Blokland, et al.
(2007) defined child victims as a minimum of five years younger than
the offender. Victims who did not meet these criteria for being categorized as child victims were categorized as peer or adult victims.
Ideally, one would want to categorize child versus peer or adult victims
on the basis of the victims’ pubertal status rather than according to their
chronological ages (see Seto, 2002).
SETO AND LALUMIÈRE
542
Table 5
Antisocial Tendencies (31 Studies)
M or %
Study
Domain/variable
K ⫽ 24
Antisocial personality traits
K⫽5
Other sources of information
Abbott (1991)
Barham (2001)
Caputo et al. (1999)
Chewning (1991)
Dunning (1991)
Etherington (1993)
Flores (2003)
Franklin (2000)
Griggins (1990)
Hill (2000)
Jacobs (1999); Jacobs et al.
(1997)
Katz (1990)
Krauth (1998)
Leguizamo (2000)
Lincoln (1993)
Lindsey et al. (2001)
Mattingly (2000)
Milloy (1994, 1996)
Ness (2001)
Oliver et al. (1993)
Valliant & Bergeron
(1997)
a
Poor empathy victim
Little responsibility offensea
SRPa
BIS-11a
PSD callous–unemotionala
PSD impulsivitya
CLOIT-R hostile hemisphere
CLOIT-R friendly hemisphereb
CPI-R Empathya,b
PCL-R diagnosis
MAPI forcefula
K-SADS impulsivitya
MAPI respectfula,b
MAPI cooperativea,b
MAPI confidenta
MAPI social tolerancea
IRI total scorea,b,c
COS empathya,b
PSD callous–Unemotionala
JI aggressiona
JI value orientationa
JI alienationa
JI social maladjustmenta
JI asocial indexa
IRI-A emotional concerna,b
OSIQ impulse control scalea
BDHI reactive hostilitya
PCL-R
MMPI psychopathic deviatea
JI aggressiona
JI social maladjustmenta
JI value orientationa
JI alienationa
Demonstrated impulsivity
MACI impulsivenessa
MACI delinquent pronea
BORRTI egocentricitya
STAXI state angera
STAXI trait angera
STAXI temperamenta
STAXI represseda
STAXI anger ina
STAXI anger outa
IRI empathic concerna,b
IRI perspective takinga,b
MACI forcefula
MACI unrulya
MACI social insecuritya
MACI egotistica
MACI delinquent pronea
MACI impulsivenessa
Exploits or manipulates
ARTSa
RBQa
JI social maladjustmenta
MMPI psychopathic deviatea
BDHI assaulta
ASOs
62%
52%
274.9
71.5
35%
26%
19.5
9.0
18.4
65%
75.7
5.9
34.6
32.4
59.9
69.6
58.0
34.4
4.2
49.6
49.8
53.9
59.2
58.8
3.7
3.7
10.7
27.2
64.6
16.8
19.5
17.8
10.6
47%
62.2
68.9
59.2
16.1
22.7
10.5
11.2
18.3
19.8
13.4
11.0
39.2
65.7
67.7
51.7
71.7
60.1
39%
22.8
26.4
56.4
65.8
5.5
NSOs
68%
38%
269.9
69.8
7%
24%
16.8
9.4
19.4
0%
70.3
5.7
42.0
35.1
59.0
65.0
56.7
32.6
4.8
54.6
58.5
60.6
71.6
71.6
3.2
2.7
11.8
26.2
63.8
17.7
16.4
19.4
11.7
60%
52.1
72.9
57
18.4
26.4
10.5
9.8
18.3
19.7
17.1
12.5
38.1
66.7
71.7
56.5
73.7
57.6
34%
23.6
31.7
62.9
65.8
4.8
N
ASOs
NSOs
d
95% CI
Heterogeneity (Q)
1,114
1,522
ⴚ0.00
ⴚ0.13 to ⴙ0.13
53.4, p ⬍ .0005
363
449
0.32
ⴚ0.15 to ⴙ0.78
34.1, p ⬍ .0001
40
40
0.10
42
32
0.15
23
46
0.35
20
20
0.19
55
20
53
20
0.25
0.43
30
34
⫺0.59
30
26
26
78
29
26
110
78
⫺0.60
0.45
⫺0.33
0.14
31
34
⫺0.05
186
62
62
75
30
134
46
46
53
28
⫺0.24
0.14
⫺0.12
27
27
0.58
117
126
⫺0.13
59
47
197
90
0.04
⫺0.37
50
16
100
13
⫺0.49
⫺0.11
MALE ADOLESCENT SEXUAL OFFENDING
543
Table 5 (continued)
M or %
Study
Van Ness (1984)
Van Wijk, Vreugdenhil,
et al. (2007)
Zakireh (2000); Zakireh et
al. (2008)
Domain/variable
BDHI negativisma
BDHI suspiciona
BDHI irritabilitya
BDHI verbal hostilitya
BDHI indirect hostilitya
BDHI resentmenta
Antisocial tendenciesa
IAC poor anger controla
Thrill and adventure seekinga
Disinhibitiona
Impulsivitya
MASA PCLa
MACI antisocial clustera
MASA pervasive angera
N
ASOs
NSOs
ASOs
NSOs
d
2.4
5.4
4.8
8.1
3.6
3.8
35.5
62%
6.4
2.9
3.7
2.0
39.0
1.4
2.8
5.8
5.1
8.1
4.8
3.5
37.0
26%
6.6
4.2
3.8
2.1
45.9
1.3
29
17
17
17
49
50
49
27
161
162
163
47
49
47
0.69
⫺0.23
95% CI
Heterogeneity (Q)
⫺0.18
K ⫽ 12
Antisocial attitudes/beliefs
421
548
ⴚ0.17
ⴚ0.47 to ⴙ0.13
55.2, p ⬍ .0001
K⫽9
Toward sex, women, sexual
offending
336
412
ⴚ0.09
ⴚ0.46 to ⴙ0.27
46.8, p ⬍ .0001
K⫽4
Nonsexual attitudes/beliefs
115
170
ⴚ0.46
ⴚ0.79 to ⴚ0.12
5.3, p ⫽ .15
0.13
⫺0.64
0.17
⫺0.13
Barham (2001)
Butler & Seto (2002)
Caputo et al. (1999)
Davis-Rosanbalm (2003)
Epps (2000)
Flores (2003)
Griggins (1990)
Hill (2000)
Racey et al. (2000)
a
TATSA
CSS-Ma
SATWSa
NOBAGS beliefs about
aggressiona
Hostile attribution bias in
vignettesa
Dominance goal in conflict
vignettesa
Revenge goal in conflict
vignettesa
PCQ expected aggression
outcomea,b
ARVSa
BRMASa
Cognitive distortions–sexa
HITQ rationalizationsa
Sexual play with kids okay if
gentlea
Children can make decisions
about sexa
Conservative, exploitative
attitudes about sexa
RMASa
Attitudes about sex with
childrena
37.7
15.2
175.5
1.6
36.5
22.1
169.9
1.6
42
31
23
36
32
80
46
42
0.3
0.1
38
42
10.5
11.9
38
42
11.8
11.2
37
43
2.1
1.9
39
46
41.7
60.6
3.0
57.9
19%
37.6
48.5
5.2
69.5
0%
54
54
0.72
30
34
⫺0.62
26
26
0.24
65%
62%
3.6
3.2
36.4
13.1
42.6
19.9
26
36
110
38
⫺0.48
⫺1.07
20.6
17.4
1.2
24.5
16.4
1.3
16
50
49
13
25
47
⫺0.49
0.19
⫺0.19
Valliant & Bergeron
(1997)
Wong (2002)
Zakireh (2000); Zakireh et
al. (2008)
CPS attitudes toward drugsa
ATSVSa
MASA hostility towards
womena
K⫽8
Antisocial associations
535
708
ⴚ0.45
ⴚ0.71 to ⴚ0.19
29.2, p ⬍ .0005
K⫽3
Self-report only
293
260
ⴚ0.72
ⴚ0.89 to ⴚ0.55
0.1, p ⫽ .95
K⫽5
Other sources of information
242
448
ⴚ0.27
ⴚ0.58 to ⴙ0.03
13.6, p ⬍ .05
32
54
82
54
⫺0.93
0.02
Butler & Seto (2002)
Epps (2000)
d
YO-LSI peer relations
YO-LSI peer relationsd
3.1
4.7
5.1
4.7
(table continues)
SETO AND LALUMIÈRE
544
Table 5 (continued)
M or %
Study
Ford & Linney (1995)
Krauth (1998)
Krupica (1997)
Milloy (1994, 1996)
Ness (2001)
Wong (2002)
Domain/variable
High peer delinquencya
Gang affiliateda
Gang membershipa
Gang affiliation
Gang involvement
No. delinquent friends
N
ASOs
NSOs
ASOs
NSOs
d
13%
20%
50%
14%
4%
3.0
50%
52%
85%
23%
9%
4.2
35
218
40
59
47
50
26
194
40
197
90
25
⫺0.79
⫺0.71
⫺0.74
⫺0.17
⫺0.11
⫺0.23
95% CI
Heterogeneity (Q)
Note. ASOs ⫽ Adolescent sex offenders; NSOs ⫽ adolescent non-sex offenders; CI ⫽ confidence interval; ARTS ⫽ Adolescent Risk-Taking Scale;
ARVS ⫽ Attitudes Towards Rape Scale; ATSVS ⫽ Attitudes Towards Sex and Violence Scale; BDHI ⫽ Buss–Durkee Hostility Inventory; BIS-11 ⫽
Barratt Impulsiveness Scale-11; BORRTI ⫽ Bell Object Relations and Reality Testing; BRMAS ⫽ Burt Rape Myth Acceptance Scale; CLOIT-R ⫽
Checklist of Interpersonal Transactions—Revised; COS ⫽ Child Opinion Survey; CPI-R ⫽ California Personality Inventory—Revised; CPS ⫽ Carlson
Psychological Survey; CSS—M ⫽ Criminal Sentiments Scale—Modified; HITQ ⫽ How I Think Questionnaire; IAC ⫽ Inventory of Anger Communication; IRI ⫽ Interpersonal Reactivity Index (A ⫽ Adolescent version); JI ⫽ Jesness Inventory; K-SADS ⫽ Schedule of Affective Disorders and
Schizophrenia for School-Aged Children; MACI ⫽ Millon Adolescent Clinical Inventory; MAPI ⫽ Millon Adolescent Personality Inventory; MASA
PCL ⫽ Multidimensional Assessment of Sex and Aggression Psychopathy Checklist; MMPI ⫽ Minnesota Multiphasic Personality Inventory; NOBAGS ⫽
Normative Beliefs About Aggression Scale; OSIQ ⫽ Offer Self-Image Questionnaire for Adolescents; PCL-R ⫽ Psychopathy Checklist—Revised; PCQ ⫽
Perceived Consequences Questionnaire; PSD ⫽ Psychopathy Screening Device; RBQ ⫽ Reckless Behavior Scale; RMAS ⫽ Rape Myth Acceptance Scale;
SATWS ⫽ Sexist Attitudes Toward Women Scale; SRP-2 ⫽ Self-Report Psychopathy; STAXI ⫽ State–Trait Anger Expression Inventory; TATSA ⫽
Teenagers’ Attitudes Towards Sexual Abuse; YO-LSI ⫽ Young Offender Level of Supervision Inventory. The sources for these scales are reported in the
original articles. Some scale names do not match the scale names given in the test manuals or original sources; we used the scale names given by study
authors for ease of verification.
a
Based on self-report only. b Reverse scored. c Two of the four subscales in the Interpersonal Reactivity Index do not directly tap empathy (Fantasy,
e.g., “I daydream and fantasize, with some regularity, about things that might happen to me” and Personal Distress, e.g., “I am usually pretty effective in
dealing with emergencies”), but only total scale score was reported in this study. d Five of 13 items pertain to delinquent peers.
2007; Wong, 2002).5 For this analysis, we calculated an average
weighted effect size for each study, combining all antisocial
variables for that study and coded in the same direction such
that a positive sign meant more delinquency risk among adolescent sex offenders who offended against only peers or adults.
Five of the six studies produced positive effect sizes, and the
overall group difference was small and statistically significant;
the weighted average d was 0.21 (95% CI ⫽ 0.05 to 0.37), with
no heterogeneity in effect sizes.
The results of these two analyses are not consistent. Although
the proportion of the sex offender sample that consisted of offenders against children was unrelated to the size of the group difference, a direct comparison of offenders against peers and offenders
against children showed that the former group scored higher on
delinquency risk variables.
Childhood Abuse and Exposure to Violence
Thirty-four studies contributed to this domain (see Table 7). We
assigned the study comparisons to six variable categories, each
representing a different form of abuse or exposure to violence. The
average effect sizes in this domain are presented in Figure 2.
Experienced sexual abuse. All but two of the 31 studies in
this variable category showed a more frequent history of sexual
abuse among adolescent sex offenders, with a significant, medium
to large average effect size (heterogeneous). The group difference
was significant regardless of whether the information was obtained
from self-report or another source. Adolescent sex offenders were
also more likely to have been sexually abused than nonoffenders in
the two small studies that compared these groups on this variable
(Chewning, 1991; Etherington, 1993).
An examination of studies that reported proportions revealed
that, on average, 46% of adolescent sex offenders and 16% of
non-sex offenders reported having experienced sexual abuse. The
corresponding values for studies based on other sources of information were 32% and 8%, respectively. These percentages should
not be interpreted as estimates of the prevalence of sexual abuse
among adolescent sex and non-sex offenders, because the operational definitions of sexual abuse varied substantially across studies. Because the same definition was used for both groups in each
study, however, the group difference can be readily interpreted.
This caveat applies to the physical abuse data as well (see below).
Calculation of average proportion of offenders who were abused
was not weighted by sample size.
5
This note applies to this and subsequent analyses of victim age. The
criteria for child victims in these direct comparison studies were as follows: at
least four (Awad & Saunders, 1991) or five years younger than the offender
(Ford & Linney, 1995; van Wijk, Blokland, et al., 2007; Wong, 2002); at least
four years younger than the offender and 12 years old or younger (Krauth,
1998); and at least five years younger than the offender and 12 years old or
younger (Aljazireh, 1994). Awad and Saunders specified that none of the
offenders against peers or adults had committed offenses against child victims,
but it was not explicitly stated whether the offenders against children had any
peer or adult victims. Similarly, it appeared, but was not explicitly stated, that
the victim age groups in Ford and Linney (1995) and Wong (2002) were
mutually exclusive. Krauth (1998) did have pure victim age groups, because
the one offender who had victims in both age categories was excluded from the
analysis. Van Wijk, Blokland, et al. (2007) classified sexual offenders according to the age of the victim in their referral offense, so offenders could have
committed offenses against victims in the other age group in their history.
Aljazireh (1994) distinguished adolescent sex offenders according to their
“predominant” victim age, so an adolescent sex offender with two child
victims and one peer-aged victim would be classified as an offender against
children; 33 of Aljazireh’s 54 adolescent sex offenders targeted only children
or only peers or adults.
MALE ADOLESCENT SEXUAL OFFENDING
545
Table 6
Substance Abuse (20 Studies)
M or %
Study
Domain/variable
ASOs
NSOs
N
ASOs
NSOs
d
95% CI
Heterogeneity (Q)
1,289
3,336
ⴚ0.38
ⴚ0.52 to ⴚ0.24
64.7, p ⬍ .0001
K ⫽ 20
Any substance abuse
K ⫽ 11
Self-report only
474
780
ⴚ0.31
ⴚ0.49 to ⴚ0.12
20.2, p ⬍ .05
K⫽9
Other sources of information
815
2,556
ⴚ0.45
ⴚ0.67 to ⴚ0.23
40.8, p ⬍ .0001
K ⫽ 10
Alcohol abuse
597
2,320
ⴚ0.41
ⴚ0.63 to ⴚ0.18
30.8, p ⬍ .0005
K ⫽ 10
Other drug abuse
631
2,528
ⴚ0.35
ⴚ0.57 to ⴚ0.16
31.5, p ⬍ .0005
Abbott (1991)
Moderate/severe alcohol abusea
Heavy drug usea
Alcohol abuse history
Drug abuse history
Substance abuse
YO-LSI substance abuse
Used druga
Used alcohola
YO-LSI substance abuse
K-SADS drug addiction scorea
Drug problema
High at time of offensea
Ever trouble for alcohol or drug
usea
Use drugsa
Use alcohola
Treated for drugs or alcohola
Substance abuse
Used alcohola
Used drugsa
MACI substance abuse
pronenessa
MACI substance abuse
pronenessa
Substance abusea
Alcohol abuse history
Drug abuse history
Alcohol abuse
Marijuana abuse
Used alcohol
Used cannabis
Used amphetamines
Used secobarbital
Used other barbiturates
Used hashish
Used inhalants
Used psychedelics
Used opioids
Used cocaine
Used diazepam
Used other drugs
40
40
⫺0.40
94
24
⫺0.62
42
32
20
32
82
20
⫺0.24
⫺0.36
⫺1.24
54
20
34
26
54
20
208
26
⫺0.72
0.29
⫺0.28
⫺0.52
216
40
194
40
⫺0.85
⫺0.20
62
46
⫺0.18
Awad & Saunders (1991)
Barham (2001)
Butler & Seto (2002)
Chewning (1991)
Epps (2000)
Etherington (1993)
Fagan & Wexler (1988)
Griggins (1990)
Krauth (1998)
Krupica (1997)
Leguizamo (2000)
Mattingly (2000)
Miller (1997)
Milloy (1994, 1996)
Ness (2001)
Tinklenberg et al. (1981)
Van Wijk, Blokland, et al.
(2007)
Van Wijk, Vreugdenhil, et
al. (2007)
Zakireh (2000); Zakireh et
al. (2008)
10%
2%
9%
12%
48%
1.3
15%
25%
2.2
51.0
0%
12%
4%
30%
15%
38%
42%
62%
2.0
75%
80%
3.9
47.2
15%
27%
35%
31%
42%
0%
36%
58%
65%
63.0
54%
81%
15%
75%
70%
58%
68.3
55.5
56.9
117
126
⫺0.09
68%
62%
62%
19%
26%
97%
90%
70%
65%
33%
63%
60%
49%
33%
38%
2%
5%
92%
86%
88%
43%
57%
98%
94%
72%
68%
34%
63%
52%
51%
35%
40%
1%
5%
50
59
50
197
⫺0.57
⫺0.53
47
90
⫺0.52
63
230
⫺0.00
Any substance abuse
27%
44%
208
1,653
⫺0.21
DISC any substance disordera
MACI substance abuse
pronenessa
27%
58%
15
155
⫺0.32
6.6
7.5
50
49
⫺0.43
Note. ASOs ⫽ adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; CI ⫽ confidence interval; DISC ⫽ Diagnostic Interview Schedule for
Children; K-SADS ⫽ Schedule of Affective Disorders and Schizophrenia for School-Aged Children; MACI ⫽ Millon Adolescent Clinical Inventory;
YO-LSI ⫽ Young Offender Level of Supervision Inventory. The sources for these scales are reported in the original articles. Van Wijk, Blokland, et al.
(2007) also reported data on alcohol and other drug abuse separately.
a
Based on self-report only.
SETO AND LALUMIÈRE
546
Table 7
Childhood Abuse and Exposure to Violence (34 Studies)
M or %
Study
Domain/variable
ASOs
NSOs
N
ASOs
NSOs
d
95% CI
Heterogeneity (Q)
K ⫽ 31
Experienced sexual abuse
1,894
2,449
0.62
0.46 to 0.77
154.0, p ⬍ .0001
K ⫽ 18
Self-report only
1,108
1,360
0.67
0.43 to 0.97
113.4, p ⬍ .0001
K ⫽ 12
Other sources of information
732
1073
0.54
0.39 to 0.68
19.6, p ⫽ .05
Abbott (1991)
Aljazireh (1994)
Awad & Saunders (1991)
Benoit & Kennedy (1992)
Briley (2004)
Capozza (1997)
Chewning (1991)
Daleiden et al. (1998);
Hilliker (1997)
Davis-Rosanbalm (2003)
Epps (2000)
Etherington (1993)
Fagan & Wexler (1988)
Fleming et al. (2002)
Flores (2003)
Ford & Linney (1995)
Frazier (1999)
Griggins (1990)
Hill (2000)
Krauth (1998)
Krupica (1997)
Lee (1994)
Leguizamo (2000)
Macri (2000)
Miller (1997)
Milloy (1994, 1996)
Ness (2001)
Truscott (1993)
Van Wijk, Vreugdenhil, et
al. (2007)
Veneziano et al. (2004)
Wong (2002)
Zakireh (2000); Zakireh et
al. (2008)
a
Sexual abuse
Sexual abuse history
Sexual abuse history
Sexual abuse history
MASA sexual abusea
Ever sexually molesteda
Unwilling sexual experiencea
18%
61%
12%
26%
4.9
36%
70%
18%
25%
0%
8%
4.3
7%
5%
40
54
94
50
51
57
20
40
16
24
50
19
54
20
0.00
0.56
0.25
0.44
1.41
0.67
1.58
Child sexual abusea
Sexually abused
Sexually abused in family
Sexually abused outside family
Sexually abuseda
Sexually abused (CPS record)
Sexually abuseda
Sexually abused
Sexually abused
Sexually abuseda
Ever molested (or attempted)a
Sexually abused
Nonfamily sexual abuse
Family sexual abuse
Sexual abuse historya
Sexually abused by parentsa
CTQ Sexual Abusea
SAEQa
Sexually abuseda
Sexually abused
Incest victim
Nonincest sexual abuse
Sexually abuseda
63%
34%
20%
39%
60%
9%
2.7
43%
38%
90%
27%
50%
11%
10%
33%
3%
69%
73%
46%
39%
11%
40%
44%
7%
3%
4%
9%
5%
1%
1.6
9%
17%
42%
23%
14%
4%
4%
8%
3%
40%
38%
14%
11%
0%
8%
17%
289
29
54
138
32
54
1.20
0.78
0.58
20
34
161
30
35
30
26
26
214
213
40
34
75
62
50
59
47
20
208
196
34
26
36
26
110
190
186
40
35
53
64
50
197
90
1.26
0.31
1.23
0.78
0.39
1.06
0.00
0.70
0.24
0.58
0.00
0.58
0.71
0.69
0.62
0.64
23
130
0.43
Incest abuse history
Sexually abused
Sexual abusea
7%
62%
50%
2%
18%
32%
30
60
50
365
60
25
0.12
0.94
0.29
MASA sexual abusea
54%
0%
50
49
1.44
1,131
1,269
0.19
0.04 to 0.34
52.0, p ⬍ .0001
a
K ⫽ 20
Experienced physical abuse
K ⫽ 11
Self-report only
544
636
0.24
0.09 to 0.40
15.3, p ⫽ .11
K⫽8
Other sources of information
533
617
0.05
ⴚ0.04 to ⴙ0.25
14.5, p ⬍ .05
Abbott (1991)
Aljazireh (1994)
Awad & Saunders (1991)
Benoit & Kennedy (1992)
Briley (2004)
Chewning (1991)
Epps (2000)
Etherington (1993)
Fleming et al. (2002)
Flores (2003)
Frazier (1999)
a
Physical abuse
Physical abuse history
Physical abuse history
Physical abuse history
MASA physical abusea
Disciplined by beatinga
Physically abused in family
Physically abused outside of
family
Physically abuseda
Physically abuseda
Physically abused
Physically abuseda
20%
70%
28%
40%
21.9
1.6
24%
2%
28%
12%
12%
44%
20.8
1.5
28%
2%
40
54
94
50
51
20
54
40
16
24
50
19
20
54
⫺0.12
1.03
0.24
⫺0.04
0.09
0.04
⫺0.04
45%
2.8
50%
100%
10%
2.2
21%
86%
20
161
30
30
20
196
34
36
0.71
0.49
0.57
0.42
MALE ADOLESCENT SEXUAL OFFENDING
547
Table 7 (continued)
M or %
Study
Hill (2000)
Krauth (1998)
Krupica (1997)
Lee (1994)
Leguizamo (2000)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Ness (2001)
Truscott (1993)
Zakireh (2000); Zakireh et
al. (2008)
Domain/variable
ASOs
NSOs
ASOs
NSOs
d
Physically abused
Physical abuse
Physical abuse historya
Hit by parenta
CTQ physical abusea
46%
17%
43%
29%
89%
36%
29%
37%
40%
75%
26
215
40
34
75
110
185
40
33
53
0.12
⫺0.28
0.07
⫺0.17
0.33
Ever physically abused
Physically abused
Physically abuseda
76%
28%
83%
64%
22%
73%
17
47
23
70
90
130
0.14
0.09
0.11
MASA physical abusea
66%
45%
50
49
0.39
327
292
0.24
K⫽4
Exposed to or presence of
sexual violence in family
Frazier (1999)
Griggins (1990)
Witness sexual abusea
Family member involved in
sexual offensea
Sex offender in family
Exposure to molestationa
Exposure to adults forcing sex
on other adultsa
Krauth (1998)
Leguizamo (2000)
K⫽8
Exposed to or presence of
nonsexual violence in
familyb
Abbott (1991)
Caputo et al. (1999)
Fagan & Wexler (1988)
Flores (2003)
Ford & Linney (1995)
Witness spousal abusea
M-CTS witness violencea
Sibling abuse
Witness domestic violence
Relative killing peta
Relative fightinga
Witness family violencea
Witness family violence
Mother hurt in domestic
violencea
Frazier (1999)
Krauth (1998)
Lee (1994)
N
57%
46%
22%
54%
30
26
36
26
0.68
⫺0.08
10%
0.5
0.8
4%
0.3
0.8
196
75
177
53
0.20
0.18
399
582
0.11
40
23
34
30
35
40
46
208
34
26
⫺0.35
0.21
0.22
⫺0.02
0.11
30
174
33
36
157
35
0.07
0.08
0.60
165
273
ⴚ0.14
18%
56%
11%
57%
17%
17%
82%
26%
68%
35%
43%
3%
59%
4%
17%
76%
22%
36%
K⫽5
Exposed to nonsexual violence
outside familyb
Briley (2004)
Davis-Rosanbalm (2003)
Exposure to violencea
Frequency exposure serious
violencea
Witness nonfamily violencea
Exposure to violencea
73.0
2.8
87.0
2.9
51
44
19
51
⫺0.46
⫺0.05
93%
27.0
91%
30.2
30
26
36
110
0.04
⫺0.37
Witness extreme violence
79%
63%
14
57
0.18
Frazier (1999)
Hill (2000)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
95% CI
Heterogeneity (Q)
0.01 to 0.46
4.7, p ⫽ .19
ⴚ0.03 to ⴙ0.26
7.6, p ⫽ .37
ⴚ0.37 to ⴙ0.08
4.4, p ⫽ .36
K ⫽ 11
Experienced emotional abuse
or neglect
562
709
0.28
0.05 to 0.50
34.9, p ⬍ .0005
K⫽7
Self-report only
405
421
0.25
0.02 to 0.49
14.6, p ⬍ .05
K⫽4
Other sources of information
157
288
0.34
ⴚ0.09 to ⴙ0.87
Abbott (1991)
Chewning (1991)
Emotional abusea
Disciplined by shouting or
insultsa
Emotional abuse in family
Neglect
Emotionally abuseda
Emotional neglecta
Neglect
Emotionally abuseda
Epps (2000)
Fleming et al. (2002)
Flores (2003)
Frazier (1999)
30%
2.0
35%
2.4
40
20
40
20
⫺0.05
⫺0.36
17%
24%
2.7
2.4
27%
100%
7%
20%
2.1
2.0
24%
92%
54
54
0.14
161
196
0.48
30
30
34
36
0.00
0.25
20.3, p ⬍ .0005
(table continues)
SETO AND LALUMIÈRE
548
Table 7 (continued)
M or %
Study
Hill (2000)
Leguizamo (2000)
Ness (2001)
Van Ness (1984)
Zakireh (2000); Zakireh et
al. (2008)
N
Domain/variable
ASOs
NSOs
ASOs
NSOs
d
Neglect
CTQ physical neglecta
CTQ emotional neglecta
Neglect
Emotional abuse
Intrafamily violence or neglecta
38%
63%
61%
45%
23%
41%
1%
64%
55%
39%
21%
15%
26
75
110
53
1.18
0.05
47
90
0.05
29
27
0.53
68%
37%
50
49
0.61
a
MASA psychological abuse
95% CI
Heterogeneity (Q)
Note. ASOs ⫽ Adolescent sex offenders; NSOs ⫽ adolescent non-sex offenders; CI ⫽ confidence interval; CPS ⫽ Child Protective Services; CTQ ⫽
Childhood Trauma Questionnaire; MASA ⫽ Multidimensional Assessment of Sex and Aggression; M-CTS ⫽ Modified Conflict Tactics Scales; SAEQ ⫽
Sexual Abuse Exposure Questionnaire. The sources for these scales are reported in the original articles.
a
Based on self-report only. b Some variables in this domain may also include exposure to sexual violence.
Most studies reported rates of sexual abuse, so we also calculated an odds ratio for each study and an overall weighted odds
ratio for the set of studies. Twenty-nine studies reported the
number (or percentage) of the two groups of adolescent offenders
who had been sexually abused, for an overall odds ratio of 5.54
(95% CI ⫽ 4.00 to 7.69). Studies based on self-report only (k ⫽
16) obtained an average odds ratio of 5.35 (95% CI ⫽ 3.10 to
9.24), and studies based on other sources of information (k ⫽ 12)
obtained a similar average odds ratio of 5.75 (95% CI ⫽ 4.10 to
8.06). The source of information was unclear for one study (Aljazireh, 1994). These results show that adolescent sex offenders
had more than five times greater odds than adolescent non-sex
offenders for having been sexually abused, according to either
self-report or other sources of information.
Experienced physical abuse. A majority of the 20 studies in
this category showed a higher prevalence of physical abuse among
adolescent sex offenders. The average effect size was significant,
small, and heterogeneous. The average group difference was positive and significant for studies using self-report, but not for studies
using other sources of information. There was little heterogeneity
left after distinguishing studies by source of information. An
examination of studies that reported proportions revealed that, on
average, 59% of adolescent sex offenders and 49% of non-sex
offenders reported having experienced physical abuse. The proportions for studies based on other sources of information were
37% and 30%, respectively.
Because most studies reported rates of physical abuse, we also
calculated an odds ratio for each study and an overall weighted
odds ratio. Seventeen studies reported the number (or percentage)
of the sample who had been physically abused, for an average odds
ratio of 1.60 (95% CI ⫽ 1.05 to 2.43). Studies based on self-report
only (k ⫽ 8) obtained an overall odds ratio of 1.67 (95% CI ⫽ 0.95
to 2.92) and studies based on other sources of information (k ⫽ 8)
obtained an average of 1.24 (95% CI ⫽ 0.74 to 2.08). The source
of information was unclear for one study (Aljazireh, 1994).
Sixteen studies reported rates of abuse for both sexual and
physical abuse. Among these studies, the average odds ratio for
sexual abuse was 4.81 (3.30 to 7.01), and the average odds ratio for
physical abuse was 1.60 (1.03 to 2.48). These results are similar to
those obtained for studies that reported rates of only sexual abuse
Figure 2. Childhood abuse and exposure to violence. Number of effect sizes are indicated within parentheses.
More positive effect sizes indicate that adolescent sex offenders scored higher than adolescent non-sex offenders.
Bars indicate 95% confidence intervals.
MALE ADOLESCENT SEXUAL OFFENDING
or only physical abuse and show that the average group difference
was much greater for sexual abuse than for physical abuse.
Exposure to (or presence of) sexual or nonsexual violence in
the family. Three of the four studies reporting on exposure to (or
presence of) sexual violence in the family, involving other individuals, showed that adolescent sex offenders had higher scores,
with an average effect size that was significant, small, and homogeneous. Three studies in this category relied on self-report.
Six of the eight studies that reported on exposure to (or presence
of) nonsexual violence in the family, involving other individuals,
reported higher percentages among the adolescent sex offenders,
but this group comparison was not statistically significant. It is
possible that two of the summary scores included under “exposure
to nonsexual violence” also included sexual behaviors, because
spousal abuse (Abbott, 1991) and sibling abuse (Fagan & Wexler,
1988) could include sexual abuse, so this comparison may not be
purely about nonsexual violence.
Exposed to nonsexual violence outside of the family. There
was no difference between the groups in the five studies that
reported information in this variable category.
Experienced emotional abuse or neglect. Nine of the eleven
studies reported a greater prevalence of emotional abuse or neglect
among adolescent sex offenders. The average effect size was positive,
small to medium, significant (except for the small number of studies
that used other sources of information), and heterogeneous.
Experience of abuse and victim age. Fifteen studies included
in the categories of sexual abuse and physical abuse provided information about the proportion of the adolescent sex offender sample
who had offended against child victims; the rest of the sample offended against peers or adults. Using the same analytical procedure
we used to examine the impact of victim age on delinquency risk
variables, we calculated the correlation between the proportion of the
adolescent sex offenders who had targeted children and the effect
sizes for variables pertaining to sexual abuse (k ⫽ 15) and physical
abuse (k ⫽ 11). The proportion of the adolescent sex offenders who
had targeted children varied from .41 to 1.0 across the 15 studies.
Partial correlations, statistically controlling for sample size,
were r(12) ⫽ .25, p ⫽ .40, for sexual abuse and r(8) ⫽ ⫺.47, p ⫽
.17, for physical abuse, respectively. These results indicate that the
proportion of adolescent sex offenders against children was not
significantly related to the size of the effect for sexual or physical
abuse; there was a tendency for more positive effects for sexual
abuse when the proportion was large and the opposite tendency for
physical abuse. A similar pattern of results was obtained when the
proportion of adolescent sex offenders with child victims and
sample size were log-transformed: r(12) ⫽ .25, p ⫽ .40, sexual
abuse; r(8) ⫽ ⫺.51, p ⫽ .14, physical abuse.
We then examined the seven studies that provided data on at
least one sexual or physical abuse variable separately for sex
offenders against at least one child and offenders against only
peers or adults (Aljazireh, 1994; Awad & Saunders, 1991; Epps,
2000; Ford & Linney, 1995; Krauth, 1998; Lee, 1994; Wong,
2002). For this analysis, we calculated an average weighted effect
size for each study, combining all variables pertaining to sexual
abuse and then all variables pertaining to physical abuse. There
were too few studies to examine other forms of abuse or exposure
to violence in this way. All effect sizes were coded such that a
positive sign meant that more abuse was reported for adolescent
sex offenders who targeted peers or adults. The weighted average
549
d for the seven studies reporting on sexual abuse was ⫺0.30 (95%
CI ⫽ ⫺.48 to ⫺.12), indicating that sex offenders against peers or
adults scored significantly lower on sexual abuse variables than
sex offenders against children. The average d was ⫺0.11 for the
five studies reporting on physical abuse (95% CI ⫽ ⫺.30 to ⫹.09),
suggesting no group difference.
The results of these two different analyses of the relationship
between victim age and sexual abuse were somewhat consistent:
The correlational analysis suggested that the (sex offender vs.
non-sex offender) group difference on sexual abuse was larger
when the proportion of offenders against children among sex
offenders was high, and that sex offenders against children had
been more often sexually abused than sex offenders against peers.
With regard to physical abuse, the correlational analysis suggested
that groups with more offenders against children were nonsignificantly less likely to have been physically abused, relative to
non-sex offenders, whereas the direct comparison analysis suggested no difference between the two victim age subgroups.
Family Problems
Twenty-nine studies contributed to this diverse domain, comprising four variable categories (see Table 8). The average effect
sizes appear in Figure 3.
Relationship, communication, or satisfaction problems.
This category contained variables pertaining to problematic family
relationships, communication, and satisfaction (15 studies), including variables specifically having to do with childhood attachment. There was no significant difference between the two groups.
We focused further on the four studies that reported specifically on
the relationship between the adolescent and his parents and found
no difference between the two groups.
Separation from a parent. This category contained variables
pertaining to not having lived with both biological parents for any
reason, including parental separation or divorce (16 studies). Many
adolescents were separated from one or both of their biological
parents, and there was no significant group difference in this
category.
Familial substance abuse. In this category, four of the five
studies showed a higher prevalence of substance abuse among the
families (predominantly parents) of adolescent non-sex offenders,
but the average effect size was small, non-significant, and heterogeneous.
Familial criminality. Finally, in the fourth category, seven of
eight studies reported a greater prevalence of criminality in the
family of non-sex offenders, but this group difference was small
and not statistically significant. Familial criminality was common
in both groups.
Family problems and victim age. Twelve studies included in
the domain of Family Problems provided information about the
proportion of the adolescent sex offender sample who offended
against at least one child; the other adolescent sex offenders had
peer or adult victims only. For this analysis, we calculated, for
each of the 12 studies, an average weighted effect size for all
family problems variables. We then correlated these study-average
effect sizes with the study proportions of adolescent sex offenders
who offended against children. The proportions of offenders with
child victims ranged from .41 to 1.0 across the 12 studies.
SETO AND LALUMIÈRE
550
Table 8
Family Problems (29 Studies)
M or %
Study
Domain/variable
ASO
NSO
N
ASO
NSO
d
95% CI
Heterogeneity (Q)
K ⫽ 15
Relationship, communication,
satisfaction problems
917
1,490
ⴚ0.01
ⴚ0.34 to ⴙ0.32
183.6, p ⬍ .0001
K ⫽ 11
Self-report only
583
942
0.14
ⴚ0.13 to ⴙ0.41
51.2, p ⬍ .0001
K⫽6
Other sources of information
420
636
ⴚ0.23
ⴚ0.83 to ⴙ0.38
101.3, p ⬍ .0001
K⫽5
Parent–child relationship
190
223
0.06
ⴚ0.50 to ⴙ0.61
29.5, p ⬍ .0001
Abbott (1991)
FACES perceived family dysfunctiona
FACES nonbalanced adaptabilitya
FACES nonbalanced cohesiona
Dissatisfaction with familya
PACS adolescent little openness with
mothera,b
PACS adolescent very problematic
with mothera,b
PACS adolescent little openness with
fathera,b
PACS adolescent very problematic
with fathera,b
Emotionally distant from parentsa,b
FACES mother’s perceived family
dysfunction
FACES father’s perceived family
dysfunction
FACES mother nonbalanced
adaptability
FACES father nonbalanced
adaptability
FACES mother’s nonbalanced
cohesion
FACES father’s nonbalanced cohesion
Mother’s dissatisfaction with family
Father’s dissatisfaction with family
PACS mother little openness with
adolescentb
PACS mother very problematic with
adolescentb
PACS father little openness with
adolescentb
PACS father very problematic with
adolescentb
Family environmenta
YO-LSI family problemsc
YO-LSI family problemsc
PRQa,b
MAPI family rapporta
FPSCI affirming communicationa,d
FPSCI incendiary communicationa
FACI-8 attachmenta,d
FACI-8 positive family environmenta,d
FACES cohesiona,d
Adequate adult supervisiond
Adequate disciplined
FACES adaptabilitya,d
FACES cohesiona,d
CRPBI-30 perceived mother
acceptancea,b,d
CRPBI-30 perceived father
acceptancea,b,d
MACI family discorda
Unsatisfactory family relations
⫺0.20
Briley (2004)
Butler & Seto (2002)
Epps (2000)
Etherington (1993)
Fleming et al. (2002)
Hill (2000)
Krauth (1998)
Lee (1994)
Mattingly (2000)
Milloy (1994, 1996)
10%
32%
40%
40%
14%
28%
48%
55%
52%
38%
40
40
40
40
37
40
40
40
40
40
22%
35%
37
40
19%
39%
31
34
23%
29%
31
34
62%
6%
60%
16%
40
32
40
37
24%
27%
20
15
23%
38%
32
37
19%
60%
20
15
33%
43%
32
37
38%
49%
55%
19%
38%
43%
47%
38%
20
32
20
31
15
37
15
37
23%
30%
31
37
29%
27%
21
15
24%
27%
21
15
98.1
3.0
4.7
45.4
77.3
9.4
7.8
27.8
36.1
52.1
55%
62%
42.6
52.7
25.1
100.4
3.9
4.9
36.3
61.6
10.2
6.4
29.8
39.7
49.9
8%
9%
36.9
46.9
20.7
51
32
54
19
82
54
⫺0.03
⫺0.40
0.44
20
161
20
196
0.74
0.31
26
199
204
34
34
34
110
189
185
33
33
31
⫺0.24
⫺1.23
21.4
18.3
33
28
62.3
80%
63.5
67%
117
59
126
197
⫺0.59
⫺0.06
0.21
MALE ADOLESCENT SEXUAL OFFENDING
551
Table 8 (continued)
M or %
Study
Miner (2003)
Ness (2001)
Van Wijk, Vreugdenhil, et
al. (2007)
Wong (2002)
Domain/variable
N
ASO
NSO
ASO
NSO
d
95% CI
Heterogeneity (Q)
Support from siblingsa,d
Sibling relations problems
Relatives’ relations problems
Parent–child relation problemsb
3.7
51%
28%
94%
4.5
30%
8%
90%
38
47
38
90
0.78
0.32
Parental conflicta
IPPA bonds to mothera,b,d
FAM-DRS mother–adolescent
communicationa,b,d
FAM-DRS mother–adolescent
affective expressiona,b,d
FAM-DRS mother–adolescent
involvementa,b,d
28%
89.2
59.6
39%
90.2
57.7
25
50
10
298
25
6
⫺0.09
0.05
54.4
59.0
10
6
51.4
50.7
10
6
1,162
6,722
ⴚ0.07
ⴚ0.19 to ⴙ0.04
25.2, p ⬍ .05
K ⫽ 16
Separated from one parent
K⫽7
Self-report only
270
400
ⴚ0.12
ⴚ0.42 to ⴙ0.17
16.8, p ⬍ .05
K⫽7
Other sources of information
620
6,106
0.04
ⴚ0.06 to ⴙ0.13
1.9, p ⫽ .93
Abbott (1991)
Aljazireh (1994)
Wong (2002)
Divorce
Has not lived with both biological
parents
Has not lived with both parents
Single-parent family
Parents separated or divorceda
Has not lived with both biological
parentsa
Has not lived with both biological
parents
Has not lived with both biological
parents
Biological father living in homea,d
Single-parent family
Has not lived with both biological
parents
Has not lived with both biological
parentsa
Parental separationa
Has not lived with both parents
Has not lived with both biological
parentsa
Parents separated/divorceda
K⫽5
Family substance abuse
ⴚ0.42 to ⴙ0.19
12.9, p ⬍ .05
ⴚ0.25 to ⴙ0.10
12.1, p ⫽ .10
Awad & Saunders (1991)
Barham (2001)
Chewning (1991)
Fagan & Wexler (1988)
Ford & Linney (1995)
Gregory (1998)
Griggins (1990)
Jonson-Reid & Way (2001)
Krauth (1998)
Lee (1994)
Leguizamo (2000)
Ness (2001)
Sivley (1998)
48%
78%
48%
88%
40
54
40
16
0.00
⫺0.12
56%
60%
40%
38%e
54%
72%
30%
82%
94
42
20
34
24
32
20
208
0.01
⫺0.20
0.10
⫺0.77
80%
85%
35
26
⫺0.03
60%
53%
58
116
0.12
27%
27%
77%
35%
22%
84%
26
304
218
26
5,778
200
0.08
0.06
⫺0.18
85%
91%
34
34
⫺0.09
87%
83%
58%
83%
87%
76%
75
47
31
53
90
34
0.06
⫺0.06
⫺0.33
61%
46%
50
25
0.23
285
650
ⴚ0.11
25%
32%
52%
42%
50%
58%
68%
48%
45%
27%
40
30
40
34
⫺0.64
⫺0.35
Krauth (1998)
Krupica (1997)
Van Wijk, Vreugdenhil, et
al. (2007)
Parents abuse alcohol
Biological mother substance abuse
Biological father substance abuse
Family substance abusea
Parent had substance abuse problema
147
40
177
40
⫺0.05
0.43
Parental abuse of drugsa
21%
25%
28
359
⫺0.01
K⫽8
Criminality in family
428
866
ⴚ0.07
Barham (2001)
Flores (2003)
Family criminal history
Biological mother criminality
Biological father criminality
Family criminal history
Family criminal history
Family criminal history
Parental criminal historya
42
30
32
34
⫺0.06
⫺0.18
35
58
153
33
26
116
166
35
⫺0.56
0.35
⫺0.00
⫺0.17
Abbott (1991)
Flores (2003)
Ford & Linney (1995)
Gregory (1998)
Krauth (1998)
Lee (1994)
a
31%
44%
44%
34%
50%
45%
64%
36%
56%
56%
65%
31%
45%
74%
(table continues)
SETO AND LALUMIÈRE
552
Table 8 (continued)
M or %
Study
Domain/variable
Oliver et al. (1993)
Van Wijk, Vreugdenhil, et
al. (2007)
Family criminal history
a
Parental crime history
N
ASO
NSO
ASO
NSO
d
18%
31%
50
100
⫺0.25
22%
29%
27
357
⫺0.05
95% CI
Heterogeneity (Q)
Note. ASOs ⫽ adolescent sex offenders; NSOs ⫽ adolescent non-sex offenders; CI ⫽ confidence interval; CRPBI-30 ⫽ Children’s Report of Parental
Behavior Inventory-30; FACES ⫽ Family Adaptability and Cohesion; FACI-8 ⫽ Family Attachment and Changeability Index– 8; FAM-DRS ⫽ Family
Assessment Measure—Dyadic Relationship scale; FPSCI ⫽ Family Problem Solving and Communication Index; IPPA ⫽ Inventory of Parent and Peer
Attachment; MACI ⫽ Millon Adolescent Clinical Inventory; MAPI ⫽ Millon Adolescent Personality Inventory; PACS ⫽ Parent–Adolescent Communication Scale; PRQ ⫽ Parental Relations Questionnaire (high score ⫽ more problems); YO-LSI ⫽ Young Offender Level of Supervision Inventory. The
sources for these scales are reported in the original articles.
a
Based on self-report only. b Parent– child relationship subcategory. c Seven of 14 items pertain to family problems. d Reverse scored. e Value
estimated from chi-square (31.0); d calculated from chi-square.
We found the resulting correlation, statistically controlling for
study sample size, to be r(9) ⫽ .09, p ⫽ .79. We also examined the
partial correlation when the proportion of adolescent sex offenders
with child victims and sample size were log-transformed and
obtained a similar result, r(9) ⫽ .11, p ⫽ .75.
We next focused on the seven studies providing data that allowed us to directly compare offenders against child victims and
offenders against peer or adult victims on at least one family
problems variable (Aljazireh, 1994; Awad & Saunders, 1991;
Epps, 2000; Ford & Linney, 1995; Krauth, 1998; Lee, 1994;
Wong, 2002). For this analysis, we calculated an average weighted
effect size for each study, combining all family problems variables
for a given study; all of these effect sizes were coded such that a
more positive score meant more family problems among adolescents who sexually offended against peers or adults. Six of the
seven studies produced positive effect sizes, for a weighted average d of 0.06 (95% CI ⫽ ⫺0.13 to ⫹0.24, no heterogeneity).
Overall, results from these two analyses revealed no effect of
victim age.
social isolation, and other social problems that can interfere with
the development or maintenance of relationships with others (22
studies and four variable categories; see Table 9). Variables pertaining specifically to family relationships were assigned to the
previous domain.
The results were quite consistent in this domain; the average effect
sizes appear in Figure 4. Adolescent sex offenders tended to have
more problems in all four variable categories, but only one of these
comparisons reached statistical significance, specifically, social isolation. Studies using self-report and studies based on other sources of
information produced similar results. A similar pattern of more social
difficulties was observed among the three studies that compared
adolescent sex offenders and nonoffenders on measures of social
functioning (Chewning, 1991; Katz, 1990; Valliant & Bergeron,
1997). Unfortunately, there were too few studies available to examine
the impact of victim age in this domain. Of note, the group difference
for heterosocial skills deficits was not significantly larger than for
more general social skills problems.
Interpersonal Problems
Sexuality
The interpersonal problems domain contained variables pertaining to heterosocial skills deficits, general social skills deficits,
Surprisingly, perhaps, less than a quarter of studies included in this
meta-analysis compared adolescent sex offenders with adolescent
Figure 3. Family problems. Number of effect sizes are indicated within parentheses. More positive effect sizes
indicate that adolescent sex offenders scored higher than adolescent non-sex offenders. Bars indicate 95%
confidence intervals.
MALE ADOLESCENT SEXUAL OFFENDING
553
Table 9
Interpersonal Problems (22 Studies)
M or %
Study
Domain/variable
K⫽5
Heterosocial skills deficits
Barham (2001)
Griggins (1990)
Katz (1990)
Ness (2001)
Wong (2002)
Heterosocial anxietya
Fear of heterosexual contacta
Comfort around girlsa,b
Heterosexual skillsa,b
Opposite-sex relationship problems
No. opposite-sex friendsa,b
K⫽8
Social skills deficits
Barham (2001)
Hollin & Swaffer (1993)
Social self-efficacya,b
Social problem-solving skillsa,b
Poor social skills
Perceives emotions righta,b
Assertivenessa,b
BORRTI social incompetencea
MESSY social skills deficitsa
Social problem-solving deficits
Poor social skills
Correctly read facial expressionsa,b
IPT perceptiona,b
Social problem-solvinga,b
Katz (1990)
Leguizamo (2000)
Mattingly (2000)
Milloy (1994, 1996)
Racey et al. (2000)
Risk (1993)
N
ASO NSO ASO
NSO
196
207
111.5 120.5
17.9 10.7
4.1
5.5
89.2 105.8
6%
0%
1.1
0.8
32 ⫺0.44
26
1.09
31
47
50
34
0.64
90
0.31
25 ⫺0.16
482
95% CI
0.29 ⴚ0.21 to ⴙ0.78
42
26
342
137.9 138.8
136.6 133.3
35.7 37.5
10.0 10.4
18.5 20.2
51.7 46.8
50.6 52.6
22% 22%
46% 32%
32% 43%
5.0
5.7
141.7 141.6
d
0.13 ⴚ0.04 to ⴙ0.31
42
7
32
0.04
11 ⫺0.01
31
75
75
59
34
0.23
53
0.50
100 ⫺0.19
197
0.12
36
38
17
17 ⫺0.00
Heterogeneity (Q)
23.6, p ⬍ .0005
9.9, p ⫽ .19
0.32
K ⫽ 16
Poor social relations, isolation, withdrawal,
introversion
872
1,019
0.25
0.04 to 0.46
62.1, p ⬍ .0001
K ⫽ 14
Self-report only
739
805
0.24
0.01 to 0.47
54.6, p ⬍ .0001
K⫽5
Other sources of information
256
324
0.34
0.01 to 0.67
11.7, p ⬍ .05
Awad & Saunders (1991)
Chewning (1991)
Socially isolated
Many friendsa,b
Intimacy of friendshipsa,b
No. close male friendsa,b
CPI-R sociabilitya,b
CPI-R internalitya
FIRO-B expressed inclusiona,b
Social isolation
Fewer friends than peersa
MAPI introversivea
No. friendsa,b
Felt ignored, embarrassed, left out by same
age kidsa
Ever had best frienda,b
94
20
24
20
0.41
0.82
30
55
36
53
0.01
0.64
54
54
0.64
20
26
20 ⫺0.14
26
0.08
78
0.39
34
0.23
126 ⫺0.43
126
0.19
112
197 ⫺0.01
38
0.66
Davis-Rosanbalm (2003)
Dunning (1991)
Epps (2000)
Etherington (1993)
Griggins (1990)
Jacobs (1999); Jacobs et al.
(1997)
MMPI social introversiona
Katz (1990)
Lonelinessa
Krauth (1998)
At least one close frienda,b
Mattingly (2000)
MACI introversiona
PIERS popularitya,b
Milloy (1994, 1996)
Loner behavior
Miner (2003)
No. friendsa,b
Perceived isolation from peers
No. people would go for advicea,b
Valliant & Bergeron (1997) MMPI social introversiona
Van Wijk, Vreugdenhil, et
al. (2007)
ATL extraversiona,b
Wong (2002)
No. same-sex friendsa,b
MPRI emotional bonding with peers, rated by
motherb
MPRI emotional bonding with peers, rated by
teacherb
IPPA peer attachmenta,b
48%
50%
1.8
8.7
18.4
15.8
4.0
44%
37%
38.6
2.5
4.4
21%
80%
2.8
8.9
22.0
11.1
4.5
11%
13%
42.0
4.0
5.1
85%
81%
53.8
44.1
85%
55.0
41.6
20%
8.7
14.4
7.7
56.0
50.1
42.0
66%
50.4
42.7
22%
18.4
10.5
8.7
49.2
78
31
214
117
67
59
38
5.3
2.9
18.0
5.4
2.5
16.3
15
50
10
13.7
13.6
12
16
95.0
93.1
50
25
16
13
0.55
163
0.01
25 ⫺0.12
6
(table continues)
SETO AND LALUMIÈRE
554
Table 9 (continued)
M or %
Study
Domain/variable
K⫽6
Social problems—general or other
Epps (2000)
Victim of bullying
More severe bullying than others
Peer problems
MAPI sociablea
MAPI peer securitya
MACI submissivea
Inappropriate peer relations
Peer relationship problems
Friends’ relationship problems
MPRI aggression with peers, rated by mothers
MPRI social maturity with peers, rated by
mothersb
MPRI aggression with peers, rated by teachers
MPRI social maturity with peers, rated by
teachersb
Etherington (1993)
Mattingly (2000)
Milloy (1994, 1996)
Ness (2001)
Wong (2002)
N
ASO NSO ASO
NSO
d
308
498
0.10 ⴚ0.05 to ⴙ0.24
54
54
0.29
20
20
⫺0.00
117
59
47
126
197
90
0.01
0.22
⫺0.04
10
10
6
6
0.10
12
12
16
16
59%
37%
72%
57.4
51.4
55.8
25%
58%
32%
15.3
9.0
44%
22%
56%
58.6
50.4
55.7
15%
22%
72%
15.7
7.3
17.4
8.3
16.4
9.9
95% CI
Heterogeneity (Q)
2.8, p ⫽ .73
Note. ASOs ⫽ adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; CI ⫽ confidence interval; ATL ⫽ Adolescent Temperament
Questionnaire; BORRTI ⫽ Bell Object Relations and Reality Testing; CPI-R ⫽ California Personality Inventory—Revised; FIRO-B ⫽ Fundamental
Interpersonal Relations Orientation—Behavior; IPPA ⫽ Inventory of Parent and Peer Attachment; IPT ⫽ Interpersonal Perception Task; MACI ⫽ Millon
Adolescent Clinical Inventory; MAPI ⫽ Millon Adolescent Personality Inventory; MESSY ⫽ Matson Evaluation of Social Skills in Youngsters; MMPI ⫽
Minnesota Multiphasic Personality Inventory; MPRI ⫽ Missouri Peer Relations Inventory; PIERS ⫽ Piers–Harris Self Concept Scales. The sources for
these scales are reported in the original articles.
a
Based on self-report only. b Reverse scored.
non-sex offenders on variables related to sexual development, experience, or interests (see Table 10). The average effect sizes appear in
Figure 5. Sex offenders did not have significantly less extensive
sexual experiences (e.g., number of sexual partners) than did non-sex
offenders. The two studies that reported age at first intercourse found
an earlier age of onset for adolescent sex offenders. It was not clear
from the reports of the studies whether age at first intercourse included sexual abuse experiences. If this category did include such
experiences, then one would expect the adolescent sex offenders to
have had an earlier age of onset because more of them were sexually
abused, as demonstrated in a previous analysis. Any confounding of
consenting and sexually abusive experiences in recording age at first
intercourse would affect the magnitude of the group difference for this
sexual experience variable.
There was a small and significant group difference in the eight
studies that examined exposure to sex or to pornography; adolescent
sex offenders reported more exposure. Finally, adolescent sex offenders reported significantly more atypical sexual fantasies, behaviors, or
interests, or were more often diagnosed with a paraphilia; this was a
medium to large and significant difference, with significant heterogeneity
in effect sizes. There were too few studies available, unfortunately, to
allow for examination of the impact of victim age in this domain.
Figure 4. Interpersonal problems. Number of effect sizes are indicated within parentheses. More positive effect
sizes indicate that adolescent sex offenders scored higher than adolescent non-sex offenders. Bars indicate 95%
confidence intervals.
MALE ADOLESCENT SEXUAL OFFENDING
555
Table 10
Sexuality (17 Studies)
M or %
Study
Domain/variable
K⫽9
Sexual Experience
Capozza (1996)
Age at first heterosexual
experiencea,b
Age at first intercoursea,b
Dated a girla
Kissed a girl or boya
Fondled a girl or boya
Fondled by a girl or boya
Had oral sex with a girl or boya
Penetrated a girl or boya
SHF typical consentinga
SHF atypical consentinga
Girlfriend past 6 monthsa
Has had no sexa,b
Has engaged in kissing and
hugginga
Heavy petting, touching of
genitalsa
Masturbating each othera
Oral sexa
Has had intercoursea
Ever had girlfrienda
Sexually active with appropriate
partnersa
Chewning (1991)
Daleiden et al. (1998);
Hilliker (1997)
Fagan & Wexler (1988)
Griggins (1990)
Krauth (1998)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Miner (2003)
Ness (2001)
Age first sexual intercoursea,b
No. times had sex last yeara
Multiple relations/partners
K⫽8
Exposure to sex or
pornography
Abbott (1991)
Witness sexual relationsa
Viewed pornographya
Exposure to sexual behaviora
Exposure to sexual mediaa
Saw people having sexa
Learned about sex observing
othersa
Age first exposed to
pornography magazinesa,b
Monthly or more exposure to
pornography magazinesa
Age first exposed to
pornography videosa,b
Monthly or more exposure to
pornography videoss
Exposure to naked adultsa
Exposure to naked kidsa
Exposure to adult sexa
Exposure to kid-kid sexa
Soft-core pornography before
10 years of agea
Soft-core pornography after 10
years of agea
Hard-core pornography before
10 years of agea
Hard-core pornography after 10
years of agea
Rape pornography before 10
years of agea
Briley (2004)
Chewning (1991)
Ford & Linney (1995)
Griggins (1990)
Leguizamo (2000)
ASO
N
NSO
ASO
NSO
d
95% CI
Heterogeneity (Q)
631
653
ⴚ0.13
ⴚ0.49 to ⴙ0.22
62.2, p ⬍ .0001
57
54
0.70
20
20
⫺0.14
198
124
⫺0.13
34
208
⫺0.84
26
26
⫺0.03
10.3
12.1
12.2
55%
85%
100%
90%
65%
60%
2.9
0.6
76%
22%
88%
13.7
95%
95%
100%
85%
45%
70%
3.5
0.5
91%
3%
100%
62%
92%
26
26
23%
12%
65%
77%
42%
35%
27%
81%
100%
81%
26
26
26
26
196
26
26
26
25
58
⫺0.66
11.9
5.5
6%
13.6
34.3
3%
15
38
47
35
38
90
0.76
⫺0.75
0.07
332
270
0.27
35%
90%
25%
64.0
95%
14%
40%
88%
21%
54.7
65%
4%
40
40
⫺0.03
51
19
0.14
20
35
20
26
0.66
0.14
11.3
9.8
24
23
⫺0.02
58%
26%
24
23
12.6
12.3
22
24
64%
67%
22
24
3.0
1.6
2.6
0.5
0.8
3.2
1.3
2.6
0.4
0.5
75
53
1.8
1.6
0.6
0.4
1.5
1.3
0.1
0.0
0.05 to 0.49
12.1, p ⫽ .10
0.14
(table continues)
SETO AND LALUMIÈRE
556
Table 10 (continued)
M or %
Study
Miner (2003)
Zakireh (2000); Zakireh
et al. (2008)
Domain/variable
Rape pornography after 10
years of agea
Child pornography before 10
years of agea
Child pornography after 10
years of agea
Witness actual sex before 10
years of agea
Witness actual sex after 10
years of agea
Pornography use over 3
monthsa
MASA heterosexual
pornography usea
MASA early family exposurea
K⫽8
Atypical sexual interests
Daleiden et al. (1998);
Hilliker (1997)
SHF aggressive consent sexa
SHF nonconsenting sexa
SHF deviant partnersa
SHF voyeurisma
SHF paraphilica
SHF solitary sexa
0.7
Sex with animalsa
Finds 5 year olds sexya
Finds 8 year olds sexya
Incest with siblingsa
Sexual compulsivity
Sexual preoccupation
Hypersexuality
General paraphilia
Cross-dressinga
SFQ global deviancea
Fleming et al. (2002)
Griggins (1990)
Lee (1994)
Miner (2003)
Ness (2001)
Van Wijk, Blokland, et
al. (2007)
Zakireh (2000); Zakireh
et al. (2008)
Diagnosed paraphilia
Sexual preoccupationa(all from
MASA)
Sexual compulsivitya
Bondagea
Synergism/sexual agressiona
Sadistic fantasya
Sadism pornographya
Adult–child pornographya
Atypical paraphiliasa
Exhibitionisma
Tranvestisma
Voyeurisma
N
ASO
NSO
ASO
NSO
0.2
0.2
0.0
0.0
0.1
0.0
0.3
0.2
0.6
0.6
1.7
d
1.0
38
38
0.87
1.97
1.49
50
50
0.33
1.33
1.21
1,135
3,937
0.67
0.5
1.4
0.1
0.7
0.8
3.0
0.4
14%
1.3
1.8
21%
1.1
2.5
1.7
0.8
6%
0.5
0.2
0.0
0.8
0.2
1.4
198
124
0.47
1%
0.5
0.8
0%
0.6
1.8
1.2
0.3
0%
161
26
196
26
0.54
0.51
34
38
35
38
0.63
0.72
47
90
0.31
8%
1.6
0%
1.0
557
50
3,377
50
1.37
0.66
1.2
0.4
0.2
0.2
0.4
0.3
0.8
0.5
0.3
1.0
0.5
0.2
0.1
0.0
0.7
0.1
0.4
0.2
0.1
0.2
95% CI
Heterogeneity (Q)
0.28 to 1.06
126.9, p ⬍ .0001
Note. ASOs ⫽ adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; CI ⫽ confidence interval; SFQ ⫽ Sexual Fantasy Questionnaire, SHF ⫽
Sexual History Form, MASA ⫽ Multidimensional Assessment of Sex and Aggression. The sources for these scales are reported in the original articles.
a
Based on self-report only. b Reverse scored.
Only three studies in this meta-analysis compared adolescent
sex offenders and nonoffending males on any sexual interest or
behavior variables. Chewning (1991) found that adolescent sex
offenders tended to score higher, rather than lower, on variables
reflecting conventional sexual experiences, and were more likely
to report early exposure to sex. Lee (1994) found that adolescent
sex offenders tended to be more likely to have had sexual contact
with a sibling. Daleiden et al. (1998) found that adolescent sex
offenders were more likely to report atypical sexual behaviors.
Psychopathology
The domain of psychopathology included general measures of
psychopathology and measures of more specific aspects of psychopathology such as anxiety or depression (23 studies and seven
variable categories; see Table 11 and Figure 6). Almost all psychopathology variables were based on self-report.
The pattern of results was generally consistent. Adolescent sex
offenders reported more psychopathology than non-sex offenders,
MALE ADOLESCENT SEXUAL OFFENDING
557
Figure 5. Sexuality. Number of effect sizes are indicated within parentheses. More positive effect sizes indicate
that adolescent sex offenders scored higher than adolescent non-sex offenders. Bars indicate 95% confidence
intervals.
significantly so for variables pertaining to anxiety and low selfesteem and nonsignificantly so for variables pertaining to general
psychopathology, depression, psychotic symptoms, and suicidal
tendencies. Three studies found that adolescent sex offenders
tended to score higher than nonoffenders in measures of psychopathology; non-sex offenders scored higher on neuroticism, but not
significantly so (Etherington, 1993; Katz, 1990: Valliant &
Bergeron, 1997). Consistent with the pattern of results obtained in
the interpersonal problems domain, adolescent sex offenders experienced significantly more social anxiety than did non-sex offenders, but this difference was not significantly larger than the
difference obtained for anxiety in general. Very few studies presented information on sexual victim age.
Cognitive Abilities
This broad domain, which includes 28 studies, covers general and
specific tests of intelligence, as well as academic achievement problems, learning problems, and neurological anomalies (Table 12;
Figure 7). Adolescent sex offenders had lower scores than non-sex
offenders on general intelligence, verbal intelligence, and performance intelligence, but none of the differences were significant.
However, they had significantly more learning problems or disabilities. Non-sex offenders had significantly more academic
achievement problems than did sex offenders, in keeping with their
significantly greater school behavioral problems (see conduct
problems domain). There was no difference for neurological
anomalies. The average full-scale intelligence score (14 studies),
unweighted by sample size, was 88.7 for adolescent sex offenders
and 90.1 for non-sex offenders. These results can be compared
with those obtained in Cantor et al.’s (2005) meta-analysis; Figure 6 suggests the mean intelligence score for adolescent sex
offenders was approximately 88 whereas the mean intelligence
score for non-sex offenders was approximately 90.
Intelligence and victim age. Ten studies included in the variable category of general intelligence provided information about
the proportion of the adolescent sex offender sample who offended
against at least one child (the other adolescent sex offenders had
peer or adult victims only). We correlated study effect sizes with
the proportions of adolescent sex offenders who offended against
children. The proportions of offenders with child victims ranged
from .38 to 1.0 across the 10 studies. The resulting correlation,
statistically controlling for study sample size, was r(7) ⫽ .41, p ⫽
.27. We also examined the partial correlation when the proportion
of adolescent sex offenders with child victims and sample size
were log-transformed, and a similar result was obtained, r(7) ⫽
.43, p ⫽ .25.
We next focused on the four studies that provided data allowing
for direct comparison of offenders against child victims and offenders against peer or adult victims on general intelligence variables (Awad & Saunders, 1991; Epps, 2000; Krauth, 1998; van
Wijk, Blokland, et al., 2007). The average effect size was small
and not significant, with d ⫽ 0.08 (95% CI ⫽ ⫺0.31 to ⫹ 0.47).
Overall, results from these two analyses did not reveal a significant
effect of victim age.
Impression Management
Although most studies in this meta-analysis relied on self-report as
a source of information, only six included a measure of socially
desirable responding or deliberate misrepresentation (see Table 13).
Results showed that sex offenders scored nonsignificantly lower on
measures of impression management, denial, or lying.
Publication Bias
We examined the possibility of a publication bias favouring
studies reporting significant group differences. For these analyses,
we calculated a weighted average effect size for each study within
six domains or variable categories that contained a sufficient
number of studies and that could be rationally combined into one
overall effect size: delinquency risk factors (k ⫽ 42), sexual abuse
(k ⫽ 31), family problems (k ⫽ 29), interpersonal problems (k ⫽
22), psychopathology (k ⫽ 23), and general intelligence (k ⫽ 19).
All variables were coded in the same direction, so that a positive
weighted average effect size would indicate that adolescent sex
SETO AND LALUMIÈRE
558
Table 11
Psychopathology (23 Studies)
M or %
Study
Domain/variable
ASOs
K⫽9
General psychopathology
Awad & Saunders (1991)
Van Wijk, Blokland, et al. (2007)
Van Wijk, Vreugdenhil, et al.
(2007)
Zakireh (2000); Zakireh et al.
(2008)
Moderate/severe
maladjustment
YSR internalizinga
Mental illness
Psychiatric historya
Mental health concerns
Clinical maladjustmenta
Personal adjustmenta,b
Emotional disturbancea
Mental health historya
YSR internalizinga
DISC any affective disordera
MACI social withdrawal and
lack of pleasure clustera
K ⫽ 12
Anxiety
K⫽6
Social anxiety
Butler & Seto (2002)
Epps (2000)
Miller (1997)
Milloy (1994, 1996)
Sivley (1998)
Etherington (1993)
Flores (2003)
Griggins (1990)
Jacobs (1999); Jacobs et al. (1997)
Katz (1990)
Leguizamo (2000)
Macri (2000)
Mattingly (2000)
L. C. Roberts (1997)
Valliant & Bergeron (1997)
Van Wijk, Vreugdenhil, et al.
(2007)
Zakireh (2000); Zakireh et al.
(2008)
a
NSOs
N
ASOs
NSOs
d
681
2,535
0.06
ⴚ0.03 to ⴙ0.16
6.4, p ⫽ .61
75%
94
24
0.04
55.4
4%
34%
42%
48.2
48.7
50.6
36%
55.9
0%
51.8
53.0
0%
40%
29%
53.6
44.6
51.7
34%
53.5
6%
46.8
30
54
50
59
31
75
54
50
197
34
0.19
0.14
⫺0.08
0.22
⫺0.36
290
30
16
50
1,794
358
159
49
0.04
0.11
528
670
0.28
0.16 to 0.40
7.9, p ⫽ .72
274
289
0.34
0.17 to 0.51
1.2, p ⫽ .94
20
20
0.46
30
26
78
31
34
26
78
34
0.38
0.53
0.28
0.36
62
62
46
64
0.44
0.02
117
126
0.16
67
35
16
112
31
13
0.44
⫺0.05
14
50
153
49
0.04
0.48
459
530
0.22
ⴚ0.00 to ⴙ0.45
24.7, p ⬍ .005
K-SADS panic disorder
K-SADS phobiaa
K-SADS obsessive–
compulsive disordera
K-SADS generalized anxietya
K-SADS ruminationsa
MAPI inhibiteda,c
JI social anxietya,c
OSIQ social comfort scalea,b,c
MMPI psychastheniaa
SAD social anxietya,c
JI social anxietya,c
MACI anxious feelingsa
PTSD reexperiencinga
PTSD avoidancea
PTSD arousala
MACI peer insecuritya,c
MACI inhibiteda,c
MACI anxious feelingsa
PIERS anxietya
MMPI-2 PTSD scorea
MMPI psychastheniaa
11.2
17.3
10.1
11.0
16.2
10.3
5.4
2.0
53.2
47.9
6.6
56.6
11.5
13.6
57.0
73%
50%
69%
52.7
50.2
56.0
45.9
65.5
60.9
4.4
1.3
46.2
44.1
7.7
53.5
8.7
12.8
50.0
67%
56%
64%
47.2
44.4
54.8
45.3
59.4
61.7
DISC any anxiety disordera
MACI anxious feelingsa
MACI peer insecuritya,c
14%
60.5
7.3
8%
50.5
6.6
0.28
Depression
Etherington (1993)
Flores (2003)
Jacobs (1999); Jacobs et al. (1997)
Katz (1990)
K-SADS depressiona
JI withdrawala
MMPI depressiona
BDI depressiona
JI withdrawala
MACI depressive affecta
81.4
52.7
54.0
16.3
12.4
61.5
59.0
54.2
51.8
15.6
12.5
44.7
20
30
78
31
20
34
78
34
1.34
⫺0.14
0.24
0.02
62
46
0.59
Depressive symptoms
MACI dolefula
MACI depressive affecta
Sad, withdrawn
MMPI depressiona
MACI depressive affecta
75%
55.4
56.2
19%
63.1
58.7
70%
54.7
50.1
29%
61.8
50.4
8
117
40
126
0.04
0.12
47
16
50
90
13
49
⫺0.18
0.09
0.28
Ness (2001)
Valliant & Bergeron (1997)
Zakireh (2000); Zakireh et al. (2008)
Heterogeneity (Q)
80%
K ⫽ 10
Leguizamo (2000)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Mattingly (2000)
95% CI
MALE ADOLESCENT SEXUAL OFFENDING
559
Table 11 (continued)
M or %
Study
K⫽7
Etherington (1993)
Jacobs (1999); Jacobs et al. (1997)
Katz (1990)
Mattingly (2000)
Milloy (1994, 1996)
Valliant & Bergeron (1997)
Domain/variable
ASOs
NSOs
Neuroticism
a
MAPI sensitive
MMPI hypochondriasisa
MMPI hysteriaa
Self-consciousnessa
MACI dramatizinga
Emotional instability
MMPI hypochondriasisa
MMPI hysteriaa
65.1
51.0
46.1
62.3
55.0
74%
51.0
56.4
58.0
48.7
45.8
63.0
60.0
71%
57.2
59.0
4.6
5.1
N
ASOs
NSOs
d
95% CI
Heterogeneity (Q)
ⴚ0.21 to ⴙ0.09
6.5, p ⫽ .37
ⴚ0.09 to ⴙ0.21
10.7, p ⫽ .15
ⴚ0.12 to ⴙ0.37
15.0, p ⬍ .005
0.02 to 0.46
11.5, p ⫽ .07
338
630
ⴚ0.06
20
78
20
78
0.28
0.15
31
117
59
16
34
126
197
13
⫺0.08
⫺0.26
0.04
⫺0.37
17
162
⫺0.15
868
3,892
0.06
20
20
0.68
78
78
0.27
0.03
Van Wijk, Vreugdenhil, et al.
(2007)
ATL neuroticisma
K⫽8
Psychotic symptoms
Etherington (1993)
K-SADS manic syndromea
K-SADS depersonalizationa
MMPI paranoiaa
MMPI schizophreniaa
MMPI hypomaniaa
Auditory hallucination
Visual hallucination
Other hallucination
Paranoid thoughts
Thought disorder
MACI borderline tendencya
MMPI paranoiaa
MMPI schizophreniaa
MMPI hypomaniaa
CPS thought disturbancea
Diagnosed psychosis
28.6
2.0
61.2
59.9
60.4
47%
7%
19%
73%
70%
40.2
58.9
63.3
65.1
26.4
3%
24.7
1.1
55.3
54.6
61.8
36%
30%
11%
67%
46%
37.1
63.2
59.5
63.5
30.9
5%
15
15
16
15
10
117
16
67
63
75
69
54
126
13
0.15
⫺0.13
557
3,377
⫺0.05
DISC any psychotic disordera
25%
35%
16
163
⫺0.08
5.9
6.2
50
49
⫺0.15
501
650
0.12
216
62
117
59
47
191
46
126
197
90
⫺0.12
0.62
0.22
⫺0.13
0.16
336
385
0.24
55
55
20
31
117
47
16
53
53
20
34
126
90
13
0.73
0.14
0.43
0.19
0.19
⫺0.28
50
49
0.19
Jacobs (1999); Jacobs et al. (1997)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Mattingly (2000)
Valliant & Bergeron (1997)
Van Wijk, Blokland, et al. (2007)
Van Wijk, Vreugdenhil, et al.
(2007)
Zakireh (2000); Zakireh et al.
(2008)
K⫽5
MACI borderline tendencya
Suicidal tendencies
a
Krauth (1998)
Leguizamo (2000)
Mattingly (2000)
Milloy (1994, 1996)
Ness (2001)
Suicidal ideas or attempts
MACI suicidal tendenciesa
MACI suicidal tendenciesa
Suicidal attempts/ideation
Suicidal ideation
Suicidal
K⫽7
Low self-esteem
Dunning (1991)
Etherington (1993)
Katz (1990)
Mattingly (2000)
Ness (2001)
Valliant & Bergeron (1997)
Zakireh (2000); Zakireh et al.
(2008)
a,b
CPI-R self-acceptance
CPI-R independencea,b
MAPI personal esteema
Self-esteema,b
MACI self-devaluationa
Poor self-esteem
CSEI self-esteema,b
CPS self-deprecationa
MACI self-esteem deficit
clustera
15%
38.0
32.8
19%
4%
6%
15.8
13.4
39.8
59.2
47.5
66%
69.6
19.6
4.1
20%
23.3
27.9
27%
1%
1%
18.6
15.9
45.2
66.6
42.6
54%
64.3
21.5
3.9
Note. ASOs ⫽ Adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; CI ⫽ confidence interval; ATL ⫽ Adolescent Temperament
Questionnaire; BDI ⫽ Beck Depression Inventory; CPI-R ⫽ California Personality Inventory—Revised; CPS ⫽ Carlson Psychological Survey; CSEI ⫽
Coopersmith Self-Esteem Inventory; DISC ⫽ Diagnostic Interview Schedule for Children; JI ⫽ Jesness Inventory; K-SADS ⫽ Schedule of Affective
Disorders and Schizophrenia for School-Aged Children; MACI ⫽ Millon Adolescent Clinical Inventory; MAPI ⫽ Millon Adolescent Personality Inventory;
MMPI ⫽ Minnesota Multiphasic Personality Inventory (2 ⫽ second edition); OSIQ ⫽ Offer Self-Image Questionnaire; PIERS ⫽ Piers–Harris Self-Concept
Scales; PTSD ⫽ posttraumatic stress disorder symptoms; RBPC ⫽ Revised Behaviour Problem Checklist; SAD ⫽ Social Avoidance and Distress Scale;
YSR ⫽ Youth Self-Report. The sources for these scales are reported in the original articles.
a
Based on self-report only. b Reverse scored. c Social anxiety.
560
SETO AND LALUMIÈRE
Figure 6. Psychopathology. Number of effect sizes are indicated in parentheses. More positive effect sizes
indicate that adolescent sex offenders scored higher than adolescent non-sex offenders. Bars indicate 95%
confidence intervals.
offenders had more problems than did non-sex offenders, with the
exception of general intelligence, where a positive d would indicate greater intelligence for sex offenders.
We then compared the weighted average effect size for published (peer-reviewed) and unpublished (non–peer-reviewed) studies, within each of the six domains or variable categories. For
delinquency risk factors, published studies (k ⫽ 20) produced a
mean effect size of ⫺0.16 (95% CI ⫽ ⫺0.29 to ⫺0.03), whereas
unpublished studies (k ⫽ 22) produced a mean effect size of ⫺0.22
(95% CI ⫺0.34 to ⫺0.10). Therefore, the significant group difference favoring greater delinquency risk among non-sex offenders
was obtained for both types of studies.
For sexual abuse, published studies (k ⫽ 10) produced a mean
effect size of 0.69 (95% CI ⫽ 0.39 to 1.00), whereas unpublished
studies (k ⫽ 21) produced a mean effect size of 0.63 (95% CI ⫽
0.47 to 0.78). Therefore, the significant group difference showing
a greater prevalence of sexual abuse among sex offenders was
obtained for both types of studies. For family problems, there was
no overall group difference for either published studies (k ⫽ 8),
d ⫽ ⫺0.15 (95% CI ⫽ ⫺0.38 to 0.08), or unpublished studies (k ⫽
21), d ⫽ 0.01 (95% CI ⫽ ⫺0.15 to ⫹0.17). For interpersonal
problems, published studies (k ⫽ 7) produced a mean effect size of
0.33 (95% CI ⫽ 0.15 to 0.51), whereas unpublished studies (k ⫽
15) produced a mean effect size of 0.19 (95% CI ⫽ ⫺0.02 to 0.40).
Therefore, the significant group difference showing more interpersonal problems among sex offenders was obtained only for published studies, although there was considerable overlap in the
confidence intervals. For psychopathology, published (k ⫽ 9) and
unpublished (k ⫽ 14) studies produced different mean effect sizes,
0.03 (95% CI ⫽ ⫺0.05 to ⫹0.12) and 0.16 (95% CI ⫽ 0.01 to
0.32), respectively, with unpublished studies showing more psychopathology among adolescent sex offenders. Finally, for general
intelligence, published studies (k ⫽ 11) produced a mean effect
size of ⫺0.10 (95% CI ⫽ ⫺0.26 to ⫹0.05), whereas unpublished
studies (k ⫽ 8) produced a mean effect size of ⫺0.05 (95% CI ⫽
⫺0.24 to ⫹0.14), which are comparable.
Discussion
We identified 59 studies in our literature review that compared
male adolescent sex offenders with other male adolescent offenders on general delinquency risk factors or factors identified in
special explanations of adolescent sexual offending. Although
there were many similarities between adolescent sex and non-sex
offenders, the results of this meta-analysis indicate that the general
delinquency explanation is not sufficient to understand adolescent
sexual offending. There was support for some of the factors
identified in the special explanations we reviewed. At the same
time, we did not find support for other factors, such as exposure to
nonsexual violence, family relationship problems, social incompetence, conventional sexual experiences, and antisocial attitudes
and beliefs specifically about women or about sexual offending.
Ranked by effect size, the largest group difference was obtained
for atypical sexual interests, followed by sexual abuse history, and
then criminal history, antisocial associations, and substance
abuse.6 These results have implications for theories of sexual
offending and special explanations of adolescent sexual offending.
Theories of Sexual Offending
Our findings suggest several potential areas for modification in
current theories of adolescent sexual offending. First, antisocial
attitudes and beliefs about women or about sexual offending do not
help explain why an adolescent specifically commits sexual rather
than nonsexual offenses, although this factor is included in many
theories (Hall & Hirschman, 1991, 1992; Malamuth et al., 1991;
6
Differences in effect size magnitude across domains should be interpreted cautiously, because they are not based on studies that directly
compared adolescent sex offenders and non-sex offenders using the same
study methods. Effect sizes may be different across domains because of
underlying differences in aspects of the studies contributing to those
particular domains.
MALE ADOLESCENT SEXUAL OFFENDING
561
Table 12
Cognitive Abilities (28 Studies)
M or %
Study
Domain/variable
ASOs
K ⫽ 19
General intelligence
Awad & Saunders (1991)
Caputo et al. (1999)
WISC-R FSIQc
Wechsler IQ (some tests not
specified)
WISC-III or WAIS-R IQ
WISC FSIQ
WISC-III or WAIS-R IQ
K-BIT FSIQ
Vocabulary IQ subtest of WISCIII or WAIS-R
FSIQ (estimated)
Csercsevits (2000)
Davis-Rosanbalm (2003)
Epps (2000)
Flores (2003)
Franklin (2000)
Griggins (1990)
Jacobs (1999); Jacobs et
al. (1997)
Krauth (1998)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Mattingly (2000)
Oliver et al. (1993)
Tarter et al. (1983)
Valliant & Bergeron (1997)
Van Wijk, Blokland, et
al. (2007)
Van Wijk, Vreugdenhil,
et al. (2007)
Veneziano et al. (2004)
Zakireh (2000); Zakireh
et al. (2008)
K⫽8
NSOs
N
ASOs
NSOs
d
95% CI
Heterogeneity (Q)
1,228
2,572
ⴚ0.08
ⴚ0.20 to ⴙ0.04
35.5, p ⬍ .01
ⴚ0.36 to ⴙ0.07
15.4, p ⬍ .05
ⴚ0.26 to ⴙ0.19
19.4, p ⬍ .05
0.06 to 0.32
32.9, p ⬍ .005
87.9
79.6
95.0
83.0
94
23
24
46
⫺0.48
⫺0.32
102.0
83.7
89.0
94.9
5.8
104.4
79.5
94.3
89.0
5.9
66
21
51
30
30
66
24
54
34
29
⫺0.14
0.23
⫺0.56
0.52
⫺0.05
92.4
95.6
26
26
⫺0.30
WAIS-R FSIQ
Culture Fair Test, some WISC-III
83.5
96.7
83.5
95.7
78
218
78
200
0.00
0.08
WISC IQ
Wechsler FSIQ
FSIQ (not specified)c
Peabody Picture Vocabulary Test
WISC-R or WAIS FSIQ
TONI IQ
83.2
82.2
86.8
95.7
89.7
92.1
88.8
83.0
89.3
89.6
92.7
93.7
17
120
50
14
80
145
100
59
⫺0.37
⫺0.06
⫺0.17
0.04
16
13
⫺0.17
WISC/WAIS IQd
84.2
87.5
268
1,339
⫺0.22
GIT IQ
FSIQ (not specified)
Two subtests from WISC-III or
WAIS-III
88.2
94.0
90.6
90.7
88.0
87.2
17
39
50
163
42
50
⫺0.19
0.46
0.28
365
583
ⴚ0.15
Verbal intelligence
WISC-R verbal IQ
WISC-III or WAIS-R verbal IQ
K-BIT verbal IQ
84.4
87.0
90.6
92.0
92.6
87.0
94
51
30
24
54
34
⫺0.51
⫺0.64
0.30
WAIS-R verbal IQ
82.0
82.8
78
78
⫺0.06
79.6
81.5
95.7
86.3
91.0
84.9
81.9
89.6
88.3
89.7
17
120
14
80
145
59
⫺0.35
⫺0.03
0.09
Veneziano et al. (2004)
WISC verbal IQ
Wechsler verbal IQ
Peabody Picture Vocabulary Test
WISC-R or WAIS verbal IQ
WISC-III verbal IQ
31
39
0.09
K⫽9
Performance intelligence
451
526
ⴚ0.04
Awad & Saunders (1991)
Epps (2000)
Flores (2003)
Jacobs (1999); Jacobs et
al. (1997)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Mattingly (2000)
Tarter et al. (1983)
Awad & Saunders (1991)
Epps (2000)
Flores (2003)
Jacobs (1999); Jacobs et
al. (1997)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Mattingly (2000)
Tarter et al. (1983)
Valliant & Bergeron (1997)
Veneziano et al. (2004)
a
93.8
93.8
100.0
98.0
94
51
24
54
⫺0.41
⫺0.44
100.1
93.2
30
34
0.52
WAIS-R performance IQ
88.3
87.1
78
78
0.08
WISC performance IQ
Wechsler performance IQ
WISC-R or WAIS performance IQ
TONI IQ
WISC-III performance IQ
90.4
85.6
95.6
92.1
97.0
93.6
86.2
97.1
93.7
89.8
17
120
14
16
31
80
145
59
13
39
⫺0.21
⫺0.04
⫺0.12
⫺0.17
0.54
1,378
4,789
0.19
94
42
20
24
32
20
0.46
⫺0.02
0.76
c
WISC-R performance IQ
WISC-III or WAIS-R performance IQ
K-BIT performance IQ
K ⫽ 15
Learning problems/disabilities
Awad & Saunders (1991)
Barham (2001)
Chewning (1991)
Learning problems
Special education
In special education classessr
55%
21%
60%
25%
25%
20%
(table continues)
SETO AND LALUMIÈRE
562
Table 12 (continued)
M or %
Study
Epps (2000)
Ford & Linney (1995)
Gregory (1998)
Krauth (1998)
Lee (1994)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Milloy (1994, 1996)
Ness (2001)
Tarter et al. (1983)
Van Wijk, Blokland, et
al. (2007)
van Wijk, van Horn, et
al. (2005)
Van Wijk, Vreugdenhil,
et al. (2007)
Domain/variable
N
ASOs
NSOs
ASOs
Speech or language problems
Special education
Learning problem in class
Special education
Special education
Unable to subtract serial 7
Poor memory forward
Poor memory backward
Learning disability
Special education
Learning problems
Digit span forwardb
Digit span backwardb
24%
11%
28%
28%
30%
85%
45%
82%
46%
21%
34%
5.9
4.3
6%
0%
25%
35%
18%
56%
21%
44%
49%
16%
34%
5.8
4.2
54
35
58
217
33
13
11
11
59
47
54
26
116
196
33
64
57
55
197
90
0.48
0.33
0.03
⫺0.13
0.21
0.40
14
59
⫺0.04
Diagnosed developmental delay
14%
8%
557
3,377
0.14
Special education
31%
9%
110
159
0.57
54%
39%
26
347
0.14
Special education
a
NSOs
d
95% CI
Heterogeneity (Q)
⫺0.04
0.04
K ⫽ 11
Academic achievement
problems
714
948
ⴚ0.12
ⴚ0.22 to ⴚ0.02
9.2, p ⫽ .51
K⫽7
Reading and spelling
554
606
ⴚ0.06
ⴚ0.18 to ⴙ0.06
3.3, p ⫽ .77
K⫽6
Mathematics
500
551
ⴚ0.07
ⴚ0.19 to ⴙ0.06
8.8, p ⫽ .12
Chewning (1991)
Epps (2000)
20
54
20
54
⫺0.10
0.09
20
20
⫺0.20
78
78
0.00
218
218
218
218
34
120
200
219
219
219
35
145
⫺0.29
59
47
197
90
⫺0.09
⫺0.37
Tarter et al. (1983)
Zakireh (2000); Zakireh
et al. (2008)
Repeated gradea
No. correctly read wordsa,b
Reading age (months)a,b
TABE achievementa,b
MAPI scholastic achievement
(high score ⫽ problem)a
WRAT readingb
WRAT spellingb
WRAT mathb
WRAT readingb
WRAT spellingb
WRAT mathb
Repeated or failed a grade
Failed a gradea
WRAT readingb
WRAT spellingb
WRAT mathb
Repeated two or more years
School problems
Peabody Individual Achievement
Testb
WRAT readingb
WRAT mathb
14
50
59
50
⫺0.14
⫺0.07
K⫽5
Neurological anomalies
216
258
ⴚ0.05
ⴚ0.23 to ⴙ0.14
0.3, p ⫽ .99
Epps (2000)
Head injury
Epilepsy or fit
Borderline IQ or mental
retardation
Major neurological signs
Minor neurological signs
Abnormal EEG or grand mal
seizure
Seizure history
Head injury
Etherington (1993)
Jacobs (1999); Jacobs et
al. (1997)
Krauth (1998)
Lee (1994)
Mattingly (2000)
Milloy (1994, 1996)
Ness (2001)
Ford & Linney (1995)
Lewis et al. (1979, 1981);
Rubinstein et al. (1993)
Miller (1997)
35%
63.8
129.1
6.4
45%
66.2
130.8
6.7
52.1
88.2
79.2
77.4
87.7
86.4
87.9
40%
85%
86.5
81.5
81.3
54%
87%
46.4
87.9
77.3
80.2
85.4
83.7
84.8
70%
80%
88.5
80.3
82.6
60%
98%
89.0
92.2
86.8
87.0
90.0
87.2
0.14
0.04
4%
4%
28%
7%
6%
39%
54
54
⫺0.04
35
26
⫺0.16
29%
100%
24%
42%
90%
23%
17
17
17
65
73
65
0.04
6%
36%
10%
38%
50
50
⫺0.04
MALE ADOLESCENT SEXUAL OFFENDING
563
Table 12 (continued)
M or %
Study
Veneziano et al. (2004)
N
Domain/variable
ASOs
NSOs
ASOs
NSOs
d
COWA no. of wordsb
Trail Making A
Trail Making B
Tower of London total move
Tower of London rule violations
Tower of London rule time
violations
Tower of London initiation time
Tower of London total execution
time
Tower of London total problem
solving time
25.0
21.9
52.8
36.3
0.4
0.5
27.0
22.6
63.1
34.5
0.6
0.5
60
60
⫺0.04
19.1
192.5
21.2
192.4
211.6
213.6
95% CI
Heterogeneity (Q)
Note. ASOs ⫽ Adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; CI ⫽ confidence interval; COWA ⫽ Controlled Oral Word Association
test; EEG ⫽ electroencephalogram; FSIQ ⫽ Full-Scale Intelligence Quotient; GIT ⫽ Groninger Intelligence Test; K-BIT ⫽ Kaufman Brief Intelligence
Test; MAPI ⫽ Millon Adolescent Personality Inventory; TABE ⫽ Test of Adult Basic Education; TONI ⫽ Test of Nonverbal Intelligence; WAIS ⫽
Wechsler Adult Intelligence Scale; WISC ⫽ Wechsler Intelligence Scale for Children; WRAT ⫽ Wide Range Achievement Test. The sources for these
scales are reported in the original articles.
a
Based on self-report only. b Reverse scored. c Estimated standard deviations (15.0). d Mean scores estimated from category scores.
Marshall & Barbaree, 1990; Ward & Beech, 2005). Second, the
results of this meta-analysis suggest that social isolation may play
a bigger role than social skills per se. Third, emotional problems
may play a role as well, but the results suggest the differences
mostly concern anxiety and low self-esteem rather than other
forms of psychopathology, such as depression or neuroticism.
Finally, the results suggest that atypical sexual interests should be
given more prominence in theories of adolescent sexual offending.
Demonstrating significant differences in particular domains,
however, is not a sufficient test of theoretically derived models
because these models typically posit both direct and indirect
“causal” relationships between the various variables. Structural
modeling is the most suitable statistical approach to testing these
complex relationships given that experimental assignment to
groups is restricted to intervention studies. To illustrate this ap-
proach, Knight and Sims-Knight (2003) found that a three-path
model provided a good fit in the prediction of sexual coercion by
adolescent males directed towards female peers or adult women.
The first path linked physical or verbal abuse history with antisocial and aggressive behavior and then sexual coercion. The second
path linked physical and verbal abuse to a callous, unemotional
personality, which was then linked to antisocial and aggressive
behavior as well as aggressive sexual fantasies; aggressive sexual
fantasies were then linked to sexual coercion. The third path linked
sexual abuse history to sexual preoccupation, drive, and compulsivity, which, in turn, was linked to aggressive sexual fantasies.
Nevertheless, we believe that the current meta-analysis contributes to theory building by identifying the most promising factors to
be examined in future research on adolescent sexual offending.
Testing complex models is best suited for individual studies, at
Figure 7. Cognitive abilities. Number of effect sizes are indicated in parentheses. More positive effect sizes
indicate that adolescent sex offenders scored higher than adolescent non-sex offenders. Bars indicate 95%
confidence intervals.
SETO AND LALUMIÈRE
564
Table 13
Impression Management (Six Studies)
M or %
Study
Domain/variable
ASOs
N
NSOs
ASOs
NSOs
d
95% CI
Heterogeneity (Q)
266
252
ⴚ0.07
ⴚ0.25 to ⴙ0.12
5.6, p ⫽ .35
K⫽6
Impression management
Flores (2003)
Jacobs (1999); Jacobs et al.
(1997)
Katz (1990)
Leguizamo (2000)
Valliant & Bergeron (1997)
Zakireh (2000); Zakireh et
al. (2008)
JI deniala
MMPI liea
47.5
52.3
45.6
51.7
30
78
34
78
0.19
0.08
JI deniala
BIDR impression managementa
MMPI liea
MASA Marlowe–Crownea
10.2
3.4
49.8
1.8
10.6
4.2
47.8
2.1
31
75
16
49
34
53
13
47
⫺0.12
⫺0.28
0.29
⫺0.33
Note. ASOs ⫽ Adolescent sex offenders; NSOs ⫽ adolescent non–sex offenders; CI ⫽ confidence interval; BIDR ⫽ Balanced Inventory of Desirable
Responding; JI ⫽ Jesness Inventory; MASA ⫽ Multidimensional Assessment of Sex and Aggression; MMPI ⫽ Minnesota Multiphasic Personality
Inventory.
a
Based on self-report only.
least until there are sufficient studies to conduct multivariate
meta-analyses. We expect that Knight and Sims-Knight’s (2003)
model could provide an even better fit to observed data if it
included measures of social isolation, anxiety, low self-esteem,
exposure to sex or pornography, and learning disabilities.
Special Explanation: Sexually Abused Sexual Abuser
We discuss the findings for childhood sexual abuse in detail
because of the attention this special explanation has received in the
literature (31 of the 59 studies in our review reported on this
variable, more than any other variable examined in this metaanalysis) and because it produced the second largest effect size
found in this meta-analysis. Moreover, childhood sexual abuse
may be an early correlate or a cause of an atypical developmental
trajectory with regard to peer relationships and subsequent sexual
behavior, and therefore the group difference in childhood sexual
abuse may help explain other significant group differences found
in this meta-analysis, including social relations problems and atypical sexual interests.
Although the prevalence of sexual abuse was lower when focusing on estimates based on other sources of information, the
group difference was found whether we focused on self-report or
other sources. It is possible that focusing on other sources of
information does not improve on the use of self-report, because
other sources of information might reflect a selective attention
effect. For example, clinicians may be more likely to inquire about
sexual abuse for adolescent sex offenders, because of an a priori
belief in an association between sexual abuse history and sexual
offending. The one study that relied on a retrospective search of
child welfare records also found that adolescent sex offenders
(9%) were much more likely than non-sex offenders (1%) to have
been sexually abused (Fagan & Wexler, 1988). Further bolstering
our confidence in this finding, we found similar results in a
meta-analysis of 17 studies comparing adult male sex offenders
with other kinds of adult offenders on their abuse histories (Jespersen, Lalumière, & Seto, 2009). Again, adult sex offenders were
substantially more likely to have histories of sexual abuse than
were adult non-sex offenders, but the two groups did not significantly differ in their histories of physical abuse.
Victim age. Sexual victim age might be a moderator of sexual
abuse history. Although the proportion of adolescent sex offenders
who targeted children was unrelated to the effect size for sexual
abuse, the seven studies that directly compared adolescent sex
offenders against child victims and those who sexually offended
against only peer or adult victims found that the former group had
significantly higher rates of sexual abuse. Jespersen et al. (2009)
obtained the same results in a comparison of adult sex offenders
against children and adult sex offenders against adults across 15
studies. Victim sex may be an additional moderator of the relationship between sexual abuse history and sexual offending:
Worling (1995b) found that adolescents who sexually offended
against any boys were more likely to have been sexually abused
than those who offended against only girls or against peers or
adults. We were not able to examine victim sex as a potential
moderator because too few studies reported data separately for sex
offenders with male victims and those with female victims.
There is evidence from other research that sexual abuse may
have a specific association with sexual offending. Adolescent sex
offenders who have been sexually abused show relatively greater
sexual arousal to children or coercive sex than those who have not
been sexually abused (Becker, Hunter, Stein, & Kaplan, 1989;
Becker, Kaplan, & Tenke, 1992; Hunter, Goodwin, & Becker,
1994). Seto et al. (in press) found that experiencing sexual coercion was significantly related to the later likelihood of engaging in
sexually coercive behavior in two large representative samples of
Swedish and Norwegian students, respectively. This association
continued to be statistically significant even after controlling for
the effects of antisocial behavior and conventional sexual experiences.
Possible mechanisms. The mechanisms underlying the association between sexual abuse and adolescent sexual offending are
not known. A number of investigators have suggested that aspects
of the sexual abuse such as the victim–perpetrator relationship,
nature of sexual abuse, duration, and timing of the sexual abuse are
important (Burton, 2003; Finkelhor, 1979; Hunter, Figueredo,
MALE ADOLESCENT SEXUAL OFFENDING
Malamuth, & Becker, 2003; Knight & Prentky, 1993). Burton et al.
(2002) examined a group of adolescent offenders and found that
sexually abused male youths were more likely to be in the sex
offender group if they had been abused by both men and women,
the perpetrator was related or used violence, the abuse took place
over several years, or the abuse involved penetrative acts.
There are probably individual characteristics that increase both
vulnerability to childhood sexual abuse and the likelihood of
adolescent sexual offending. For example, a sexually precocious
child may be more vulnerable to sexual abuse, thereby explaining
the link between sexual abuse and earlier onset of puberty, and
there appears to be a link between early puberty and sexual
offending such that male sex offenders undergo puberty at an
earlier age than do other males (Blanchard & Dickey, 1998). We
expect an interaction between these individual characteristics and
the experience of sexual abuse, because many sexually abused
children do not go on to sexually offend.
One characteristic that is clearly involved is sex. Female children are more likely to be sexually abused than are male children
(e.g., Finkelhor & Ormrod, 2001), yet the large majority of sex
offenders are male. The link between sexual abuse and sexual
offending may be specific to males or, at the very least, the effect
is much stronger among males. This does not mean that childhood
sexual abuse is not related to later sexual behavior among women,
because there is evidence for a significant association between
childhood sexual abuse and greater sexual preoccupation, earlier
onset of intercourse, and earlier pregnancy among women (e.g.,
Noll, Trickett, & Putnam, 2003).
If there is a causal relationship between childhood sexual abuse
and adolescent sexual offending, the existing data suggest it has to
do with the onset rather than maintenance of sexual offending,
given meta-analytic evidence that sexual abuse history is unrelated
to sexual recidivism in follow-up studies of offenders (Hanson &
Bussière, 1998; Hanson & Morton-Bourgon, 2005). In other
words, sexual abuse is associated with the likelihood that someone
commits a sexual offense for the first time, but it does not predict
who is more likely to sexually reoffend once identified. Thus,
interrupting the link between childhood sexual abuse and onset of
adolescent sexual offending may be an important goal of prevention campaigns, whereas treatment addressing sexual abuse issues
is unlikely to reduce reoffending among identified sex offenders.
Other Special Explanations
Poor childhood attachment. Contrary to the expectations of
Marshall and Barbaree’s (1990) integrated theory and other special
explanations of adolescent sexual offending emphasizing poor
childhood attachment, adolescent sex offenders did not appear to
have more family relationship problems than non-sex offenders.
The test of this prediction, however, was weak because only two
studies examined attachment specifically, and only one of these
assessed parent– child attachment. Future research with validated
measures of parent– child attachment is needed to further test the
role of parent– child attachment in adolescent sexual offending.
Social incompetence. Contrary to predictions that social incompetence plays a role in adolescent sexual offending (Finkelhor,
1984; Marshall & Barbaree, 1990; Ward & Siegert, 2002), we
found no significant difference between the two groups of adolescents on measures of heterosocial or general social skills. The two
565
groups did differ, however, on measures of social isolation, suggesting social problems do play a role, but not because of social
incompetence.
Sexual development. There was no significant difference between groups on conventional sexual experiences, but adolescent
sex offenders were significantly more likely to have had early
exposure to sex or pornography, consistent with Marshall and
Barbaree (1990).
Atypical sexual interests. As noted earlier, the largest effect
size we observed was for atypical sexual interests. The group
comparison was not ideal because adolescent sex offenders who
simply admitted to their criminal sexual behavior could score
higher on many (although not all) of these variables. Variables that
would not include sexual offending behavior, such as admitting a
sexual interest in children or cross-dressing, also showed a consistent trend in the same direction, suggesting that this result is not
tautological (higher scores on measures of atypical sexual interests
are a result of sex offenders admitting to sexual offenses). More
studies with measures of atypical sexual interests that exclude
sexual offenses would help clarify this group difference. Such
measures might include self-reported thoughts, fantasies, or urges
about paraphilic targets or activities, variables reflecting noncriminal paraphilic behavior, such as masochism or fetishism, and
psychophysiological measures of sexual arousal to atypical targets
or activities, such as prepubescent children or coercive sex
(Lalumière et al., 2005; Seto, 2008). Comparisons of adolescent
sexual and nonsexual offenders with objective psychophysiological measures would be particularly helpful, because past studies
using these measures have not included a same-aged non-sex
offender comparison group (Robinson et al., 1997; Seto et al.,
2000).
Psychopathology. Partially consistent with theories suggesting that affective dysregulation and other emotional problems play
a role in adolescent sexual offending (Hall & Hirschman, 1991,
1992; Ward & Siegert, 2002), sex offenders scored higher in
anxiety and low self-esteem; they did not, however, in other forms
of psychopathology, such as depression or neuroticism. The timing
of psychopathology symptoms was not clearly distinguished in the
studies that we examined. The symptoms could have preceded the
index sexual offenses, which would be consistent with a causal
role, but they could also be a consequence of being identified as a
sex offender (e.g., becoming more anxious and having lower
self-esteem after being arrested and charged for a sexual offense,
which currently carries much more social stigma than do most
nonsexual offenses), which would not be consistent with a causal
role. Research that clarifies timing would help elucidate the relationship between psychopathology and adolescent sexual offending (e.g., by examining records of psychiatric diagnoses or mental
health treatments that precede the index sexual offenses). Van
Wijk, Vreugdenhil, et al. (2007) did ask adolescents about the
presence of psychopathology in the six or 12 months prior to their
index arrest and found no significant differences between sex and
non-sex offenders, but their statistical power to detect a difference
was quite low because psychopathology data were available for
only 16 adolescent sex offenders.
Mental health problems are negatively associated with future
offending among adolescent offenders (Katsiyannis, Zhang, Barrett, & Flaska, 2004; Vermeiren, Schwab-Stone, Ruchkin, De
Clippele, & Deboutte, 2002), which suggests that psychopathology
566
SETO AND LALUMIÈRE
would not contribute to the maintenance of sexual offending.
Indeed, mood problems may have a protective effect. Mood problems could still play a role in onset of offending, for example, if it
led to the use of sex as a coping strategy, and if using sex as a
coping strategy is then associated with a greater likelihood of
sexual offending (Cortoni & Marshall, 2001).
Another consideration in interpreting the results of the psychopathology domain is that all of the comparisons are based on
self-report. Adolescent sex offenders may tend to report more
problems or non-sex offenders may tend to report fewer problems.
The two groups did not significantly differ on measures of impression management, however, suggesting that youths may differ in
their perceptions of problems rather than in any tendency to
deliberately misrepresent themselves.
Cognitive abilities. The results did not support the idea that
low cognitive abilities specifically increase the likelihood of adolescent sexual offending. Both offending groups scored about 10
IQ points below the population average of 100. This finding is
consistent with the general delinquency explanation, as numerous
studies have shown that IQ is associated with juvenile delinquency, such that delinquents score lower on measures of intelligence than nondelinquent peers (e.g., Moffitt & Silva, 1988). In
the small number of studies that compared sex offenders against
children with sex offenders against peers, there was no difference
in general intelligence scores, in contrast to research showing that
adult sex offenders with child victims score lower on intelligence
than do sex offenders with adult victims or non-sex offenders
(Cantor et al., 2005).
General Delinquency Explanation
The results described in the previous section suggest that general delinquency risk factors are not sufficient to explain why an
adolescent commits a sexual rather than a nonsexual crime, because there were a number of differences between sex and non-sex
offenders across theoretically meaningful domains. In addition,
adolescent sex offenders scored lower than non-sex offenders on
measures of criminal involvement, antisocial associations, and
substance use. The only published comparison of female adolescent sex and non-sex offenders we found (not included in the
meta-analysis) yielded the same pattern of results, with the female
adolescent sex offenders scoring lower than female adolescent
non-sex offenders on criminal history, school behavioral problems,
and fighting (Kubik, Hecker, & Righthand, 2002).
This pattern of results does not mean that general delinquency
risk factors do not play a role in adolescent sexual offending.
Adolescent sex offenders in this meta-analysis still had extensive
criminal histories and showed evidence of a variety of conduct
problems and antisocial tendencies to a greater extent than was
found among nonoffenders (e.g., school suspensions). Adolescent
sex offenders scored higher in antisocial tendencies than did nonoffenders in the eight studies that included these data for nonoffenders (Chewning, 1991; Etherington, 1993; Franklin, 2000;
Katz, 1990; Lincoln, 1993; Lindsey, Carlozzi, & Eells, 2001; Ness,
2001; Valliant & Bergeron, 1997), and general delinquency risk
factors also predict recidivism among adolescent sex offenders
(e.g., Gretton, Hare, & Catchpole, 2004; Gretton, McBride, Hare,
O’Shaughnessy, & Kumka, 2001). Additionally, consistent with
the general delinquency explanation, adolescent sex and non-sex
offenders were, as groups, similar to each other in terms of
self-reported conduct problems, antisocial personality traits, family problems (parental separation or divorce, familial substance
abuse, familial criminality), and IQ scores.
A surprising finding was that adolescent sex offenders were not
significantly different from non-sex offenders on measures of
antisocial personality traits, yet were lower on measures of antisocial or criminal behavior. This finding cannot be explained as a
self-report bias because the same result was obtained when we
examined the five studies that relied on other sources of information (i.e., observer ratings of antisocial personality traits). One
possibility is that adolescent sex offenders and non-sex offenders
do not differ in their self-report of antisocial personality traits but
do differ in how these traits are expressed and detected by others
as behaviors. This might explain why adolescent sex offenders did
not differ from other adolescent offenders on measures of conduct
problems that relied on self-report but scored lower when the
measures used other sources of information. Further research is
needed to determine whether the expression of antisocial tendencies by adolescent sex offenders is, in fact, less likely to be
detected and what factors might account for lesser detection.
The pattern of findings observed in general delinquency risk
factors might be obscured by a difference between adolescent sex
offenders who target peers or adults and those who target children.
Among studies that directly compared sex offenders, distinguished
according to victim age, on the same measures of delinquency risk
factors, those who sexually offended against any children scored
significantly lower than those who sexually offended against peers
or adults. There were too few studies to examine victim sex or
relationship to victim as a potential moderator of effect size. We
hope these results will encourage investigators to record and
examine the effects of victim gender, victim age, and perpetrator
relationship to victim in future research on adolescent sex offenders, as is typically done with adult sex offenders.
Meta-Analysis Limitations
In addition to the specific issues identified in our discussion of
the special explanations for adolescent sexual offending, and in
Davis and Leitenberg’s (1987) and van Wijk et al.’s (2006) reviews of the adolescent sex offender literature (predominance of
adolescent samples in custody, absence of matching of sex and
non-sex offender groups on potentially important demographic
variables such as age, reliance on self-report, the common use of
unstandardized measures, and the combination of different types of
adolescent sex and non-sex offenders), there are other limitations
to keep in mind when interpreting the results of this meta-analysis.
First, it is possible that there is an ascertainment bias such that
adolescent sex offenders are more likely to be referred for treatment
or placed in custody than are adolescent non-sex offenders, simply
because their misconduct was sexual in nature, whereas only the most
antisocial non-sex offenders are admitted to a clinical or correctional
setting. For example, van Wijk, van Horn, Bullens, Bijleveld, and
Doreleijers (2005) compared 109 adolescent sex offenders with 51
non-sex offenders on personality traits (and other individual characteristics) and found that the sex offenders scored significantly lower
on measures of impulsivity and lack of conscience. However, these
authors noted in their discussion that some referrals were made by
prosecutors on the basis of the seriousness of the alleged offense or
MALE ADOLESCENT SEXUAL OFFENDING
characteristics of the adolescent suspect. Consistent with the idea of
an ascertainment bias, van Wijk, Vreugdenhil, et al. (2007) found that
adolescent sex offenders were more than twice as likely to be courtordered into treatment than adolescent non-sex offenders and Lincoln
(1993) found that sex offenders had more experience in treatment than
non-sex offenders. On the other hand, Ness (2001) found that non-sex
offenders had more experience in treatment, and Maring (1998) found
that adolescent sex offenders still scored significantly lower than
non-sex offenders (all participants were diagnosed with conduct disorder) on scales assessing antisocial personality traits.
An ascertainment bias could contribute to the significant differences obtained in general delinquency risk factors, even when
examining data collected in the same setting for both groups. This
problem is exacerbated by the fact that the majority of studies drew
samples from equivalent rather than the same settings. Nonetheless, an ascertainment bias would not explain the significant differences we obtained in other domains in which adolescent sex
offenders scored higher than non-sex offenders—such as childhood sexual abuse, exposure to sexual violence, or atypical sexual
interests— unless it could be convincingly argued or demonstrated
that such differences contributed to the bias or that these domains
are negatively correlated with delinquency. For example, Maxfield
and Widom (1996) found that abused and neglected children were
more likely to engage in antisocial behavior as they grew up, as
compared to controls. This kind of bias could not explain, however, why the adolescent sex offenders scored lower on measures
of delinquency but higher on measures of sexual or emotional
abuse history than did other offenders.
Another potential group comparison bias is the differential
treatment that adolescent sex offenders and non-sex offenders may
receive if they participate in clinical or correctional programs.
Both sex and non-sex offender treatment programs are likely to
focus on goals such as acceptance of responsibility, problemsolving, and skills training, but the adolescent sex offenders are
also likely to participate in treatment sessions that focus on disclosure of their sexual offenses and discussions of sexuality, including their sexual experiences and interests. Thus, adolescent
sex offenders may be more willing than non-sex offenders to
disclose sexual abuse, exposure to sexual violence, and atypical
sexual interests. This does not explain, however, why adolescent
sex offenders did not differ on conventional sexual experiences, or
why the difference in sexual abuse histories was found when we
focused on sources of information other than adolescent selfreport. Also, Krauth (1998) found that non-sex offenders were
more likely than sex offenders to have missing information about
whether they were sexually active, consistent with the idea of a
bias, but there was a much smaller difference in missing information for sexual abuse history and for whether there was a sex
offender in the family.
A related potential group comparison bias is that adolescent sex
offenders might spend more time in residential treatment as a
result of their offenses and thus do not have as much opportunity
to engage in antisocial or criminal behavior than do non-sex
offenders. At the same time, non-sex offenders had a more extensive criminal history and thus were probably more likely to have
been incarcerated. Although any incarcerations they incurred may
have been brief, these times in custody add up and can also reduce
opportunity to engage in further antisocial or criminal behavior.
The studies we examined did not control for amount of opportunity
567
by matching or statistically controlling for this variable. To examine this issue, we conducted a post hoc comparison of the six
studies that used community samples of adolescents to determine
whether these studies produced similar effect sizes in the domain
of general delinquency risk factors. Five studies contributed to this
domain, producing an average effect size of ⫺0.45 (95% CI ⫺0.65
to ⫺0.25, no heterogeneity). This result suggests that adolescent
sex offenders are still less antisocial than adolescent non-sex
offenders even when recruited from the community, where ascertainment bias might be lessened. We would have liked to pursue
this analysis for other variables, but there were insufficient studies
of community samples.
Another potential group comparison bias is that some adolescent
non-sex offenders may have committed sexual offenses that were
not known to the investigators and thus were incorrectly assigned
to their study group. Fleming et al. (2002) found that 20% of their
sample of adolescent offenders admitted sexual offenses for which
they were not adjudicated, whereas Spaccarelli et al. (1997) reported that 14% of their ostensibly nonsexually offending group
admitted they had committed a sexual offense in their history. To
the extent that undetected sex offenders were present in the nonsex offender group, we would expect the group differences found
in this meta-analysis to be conservative estimates of the true
differences.
Another limitation of this meta-analysis is that there were too
few studies to examine either sexual victim age or source of
information as moderators of group differences on variables relevant to the special explanations emphasizing parent-child attachment, heterosocial skills deficits, conventional sexual experiences,
and atypical sexual interests. Even fewer studies directly compared
groups of adolescent sex offenders distinguished according to their
victims’ ages, or directly compared data obtained from self-report
with other sources of information. The apparent differences in
effect sizes based on self-report or other sources of information
reported here may actually reflect differences in study sampling or
methodology.
We also did not have the data to examine non-sex offender characteristics as moderators of group differences on variables relevant to
the special explanations. For example, it may be the case that the
patterns of results differ when comparing sex offenders with lifecourse-persistent offenders versus adolescence-limited offenders or
when comparing sex offenders with violent versus nonviolent offenders. Future research could explore these possibilities. A mixed sample
of non-sex offenders was helpful in this meta-analysis because Garber
and Hollon (1991) suggested that a heterogeneous comparison group
is appropriate when examining broad specificity, that is, whether
adolescent sex offenders differ from offenders in general on theoretically meaningful factors.
Another limitation of this meta-analysis is the impact of combining variables representing different operationalizations for calculation of effect sizes. For example, we combined variables
concerning direct exposure to sexual violence in the family (“witness sexual abuse” in Frazier, 1999, and “exposure to adults
forcing sex on other adults” in Leguizamo, 2000) and variables
concerning indirect exposure (“family member involved in sexual
offense” in Griggins, 1990, and “sex offender in family” in Krauth,
1998). It is possible that there is an effect of exposure to sexual
violence only when it is directly witnessed, but there were too few
studies to explore this possibility.
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SETO AND LALUMIÈRE
Testing Causality
Despite all of these limitations, we believe that the results of this
quantitative review make a useful contribution to the development
of a comprehensive theory of adolescent sexual offending. The
results of this meta-analysis did not allow us to determine whether
the links between aspects of sexual development and adolescent
sexual offending are causal—sexual abuse, exposure to sexual
violence, and earlier exposure to sex or pornography cause the
youth to deviate from typical sexual development in ways that
increase their likelihood of committing sexual offenses— or simply correlational—youths who differ in their sexual development
in these ways also differ in other ways that render them more
vulnerable to sexual abuse, more likely to develop atypical sexual
interests, and more likely to commit sexual offenses later in life.
We believe the field will progress in understanding the onset of
adolescent sexual offending when the causal nature of these links
is further explored through longitudinal, multivariate, and experimental research.
Our speculation is that an atypical sexual interest (an interest in
prepubescent children, or in coercive sex involving peers or adults,
or in exposing one’s genitals to unsuspecting strangers, etc.) is an
important motivation for some adolescents who commit sexual
offenses, whereas antisocial tendencies influence an adolescent’s
willingness to act upon this motivation. We base this speculation
on adult sex offender research suggesting that atypical sexual
interests, such as pedophilia, are neurodevelopmental disorders
that involve prenatal factors (e.g., Cantor et al., 2004), retrospective studies in which some adult sex offenders have admitted
that their atypical sexual interests emerged early in life, usually
before the emergence of any atypical sexual behaviors (e.g.,
Freund & Kuban, 1993), follow-up studies demonstrating that
phallometrically assessed sexual arousal to children can predict
future sexual offending among men with no known history of
sexual offenses involving contact with a child (Rabinowitz, Firestone, Bradford, & Greenberg, 2002), and research showing that
the interaction between atypical sexual interests and antisocial
tendencies is a significant predictor of sexual recidivism among
both adolescent and adult sex offenders (Gretton et al., 2004; Rice
& Harris, 1997; Seto et al., 2004).
We also speculate that atypical sexual interests may help explain
many of the other group differences observed in this meta-analysis.
This does not mean that all adolescent sex offenders have atypical
sexual interests, as phallometric studies find that only some adolescent sex offenders produce atypical sexual arousal patterns in
the laboratory (Seto et al., 2000, 2003). More studies with good
measures of atypical sexual interests are needed to determine the
proportion of adolescent sex offenders who have such interests;
research on adult sex offenders suggests a slight majority of adult
sex offenders show these interests (see Lalumière et al., 2005;
Seto, 2008). This minority of adolescents would contribute to the
pattern of observed differences between sex and non-sex offenders. For example, some adolescent sex offenders may score higher
on social isolation because they are less interested in relationships
with opposite-sex peers. Some adolescent sex offenders may score
higher on psychopathology because of their social isolation or
distress about their atypical sexual interests. Kafka (1997) and
others have suggested that paraphilias are often comorbid with
other forms of psychopathology, so some of the group difference
on psychopathology measures could be attributed to the greater
prevalence of paraphilic interests among adolescent sex offenders.
Another possibility is that the neurodevelopmental factors that
disrupt sexual preferences could also be responsible for disruptions
to other brain systems that contribute to mental health (Blanchard
et al., 2002, 2003).
We believe a parsimonious and testable theory of adolescent
sexual offending would contain two primary dimensions: general
delinquency risk factors and atypical sexual interests. Research
examining other potential factors would need to demonstrate that
any group differences are not by-products of these two dimensions,
as suggested earlier. The developmental emergence and progression of delinquency has been well-studied (e.g., Elliott, 1994;
Gottfredson & Hirschi, 1990; Loeber & Farrington, 1998; Moffitt,
1993), but developmental work on atypical sexual interests is only
beginning, and work is needed on how to integrate these two
dimensions (Lalumière et al., 2005; Seto, 2008; Seto & Barbaree,
1997).
Future Directions
More comparisons of adolescent sex offenders with both nonsex offenders and nonoffending adolescents on variables hypothesized to be specific to adolescent sexual offending would contribute greatly to theory building. The most informative study
design would include at least three groups: sex offenders, non-sex
offenders, and nonoffenders. Differences between sex offenders
and the other two groups would suggest which variables might
play a role in explaining the onset of adolescent sexual offending,
whereas differences between sex offenders and non-sex offenders
could help identify those variables that have a specific role to play
in explaining why an adolescent commits sexual offenses rather
than nonsexual offenses. For example, in some of the studies
included in this meta-analysis, both sex offenders and non-sex
offenders differed from nonoffenders in antisocial tendencies, but
these factors cannot adequately explain why an adolescent commits a sexual offense rather than a nonsexual offense because sex
offenders score significantly lower on many measures of antisocial
tendencies than do non-sex offenders. Group comparison studies
could further distinguish between types of sex offenders on the
basis of theoretical and empirical grounds, for example, sex offenders with child victims in comprison with those with peer or
adult victims. Once the key factors have been identified in comparative research, the relationships between the most promising
factors can be explored with structural modeling, as demonstrated
by Knight and Sims-Knight (2003).
The results of group comparison and structural modeling studies
could greatly inform assessment, treatment, and prevention efforts.
For assessment, the results of this meta-analysis and other theoretically informed research highlight which variables may be the
most productive in developing measures to identify individuals at
greater risk of first committing a sexual offense as an adolescent.
These variables are not necessarily the same as those that predict
recidivism among adolescent sex offenders. For example, sexual
abuse history distinguishes sex offenders from other offenders, but
it is not related to recidivism among adult sex offenders (Hanson
& Morton-Bourgon, 2005). In contrast, variables in the delinquency risk domain—age of first contact with the criminal justice
system, criminal history, conduct problems, and so forth—are
MALE ADOLESCENT SEXUAL OFFENDING
related to the likelihood of future offenses among both adolescent
and adult sex offenders. There is an established empirical literature
on risk measures for juvenile delinquents, and these measures
would likely be valid for adolescent sex offenders as well (e.g.,
Catchpole & Gretton, 2003; Schmidt, Hoge, & Gomes, 2005).
With regard to treatment, our results support the notion that
treatments designed for general delinquency can also benefit adolescent sex offenders. Further, the results identify additional
treatment targets that are not addressed in these general delinquency treatments. Two small randomized clinical trials have
shown that multisystemic therapy can significantly improve outcomes among adolescent sexual offenders in comparison with
treatment as usual (Borduin, Schaeffer, & Heiblum, 2009; Letourneau et al., 2009). Multisystemic therapy is an individualized,
intense, and empirically supported treatment that addresses individual, family, and social– contextual risk factors associated with
general delinquency. Mediational analysis suggests that improvement on clinical measures is mediated by caregiver consistency in
discipline and monitoring of negative peer relationships
(Henggeler et al., 2009). Perhaps reflecting a tendency of researchers to focus on special explanations for adolescent sexual offending, only two of the studies we examined in this meta-analysis
assessed parental supervision or discipline practices (Chewning,
1991; Krauth, 1998), even though these are well-established correlates of general delinquency (Loeber & Farrington, 1998). Future
research on the treatment of adolescent sexual offending could
benefit from a closer look at the general delinquency literature.
Letourneau et al. (2009) modified the multisystemic therapy
protocol by also addressing adolescent and caregiver denial about
the sexual offense, safety planning (e.g., reducing opportunities to
be alone with younger children if younger children were victims of
sexual offenses), and promotion of age-appropriate and healthy
peer relationships. Our results suggest that specifically addressing
atypical sexual interests could further improve short-term outcomes and possibly lead to a reduction in recidivism in the longerterm. The results of more and larger randomized clinical trials and
mechanism of change studies could also add to our theoretical
understanding of adolescent sexual offending.
For prevention, the results of this meta-analysis and further
theoretically informed research could help identify causal factors
that are amenable to intervention. Many of the variables examined
in this meta-analysis are potentially amenable to intervention. If
childhood sexual abuse is a causal factor, school-based sexual
abuse prevention programs might lower the incidence of childhood
sexual abuse and thereby reduce the incidence of sexual offending
when those children grow up and become adolescents (Gibson &
Leitenberg, 2000; Rispens, Aleman, & Goudena, 1997). Research
on the characteristics of child victims of sexual abuse could help
identify at-risk individuals who might benefit from efforts to
prevent sexual abuse or any subsequent perturbation of their sexual
development if sexual abuse does occur.
The presence or absence of significant group differences in this
meta-analysis was moderated by sexual victim age in some of our
analyses. Relatively few studies, however, directly compared adolescent sex offenders who victimized peers or adults with those
who victimized children, preventing us from examining this potentially important moderator in greater detail. Studies that have
directly compared adolescent sex offenders distinguished according to victim age (but without including a non-sex offender com-
569
parison group) have reported similar differences on variables that
we examined in this meta-analysis (e.g., Carpenter, Peed, & Eastman, 1995; Hunter et al., 2003; Hsu & Starzynski, 1990; Worling,
1995a, 1995b). Future studies should distinguish adolescent sex
offenders according to sexual victim age, to clarify the nature and
size of differences between adolescent sex offenders, non-sex
offenders, and nonoffenders. Other potential moderators—such as
victim sex, relationship to victim, and whether the adolescent is on
a life-course-persistent or adolescence-limited developmental trajectory with regard to antisocial behavior—should also be examined. The relative importance of general delinquency risk factors
and atypical sexual interests may vary across these different
groups of adolescent sex offenders, with implications for risk
assessment and intervention.
Future studies should also examine variables having to do with
sexuality. It is surprising to us that research on adolescent sexual
offending has paid relatively little attention to other aspects of
sexual development. For example, nine of 59 studies examined
conventional sexual experiences, whereas 10 studies examined
depression. Only seven studies examined paraphilic (atypical)
sexual interests. Researchers in the adolescent sex offender field
have focused on sexual abuse history (more than half of the studies
we reviewed reported data on this variable) but have paid relatively little attention to other aspects of sexuality, focusing instead
on nonsexual factors (e.g., parent– child attachment, social skills
deficits, psychopathology). Our results suggest promising directions for research on the roles of exposure to sexual violence,
exposure to sex or pornography more generally, and atypical
sexual interests (see Seto, Maric, & Barbaree, 2001). Sexual offending, after all, is a sexual as well as an antisocial behavior.
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Received March 2, 2009
Revision received February 20, 2010
Accepted February 26, 2010 䡲
Call for Papers
Psychology of Violence
Special Issue: Theories of Violence
Psychology of Violence, a new journal publishing in 2011, invites manuscripts for a special issue
on theories of violence.
Topics will include but are not limited to:
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New theoretical models
Extensions of existing models either to violence for the first time or to new forms of violence
Evaluations and critiques of existing theoretical models for a particular type of violence
Papers that compare and contrast theoretical models for more than one form of violence
Comparisons of theoretical models which examine how social and cultural factors affect the
way violence develops and manifests under different conditions.
Manuscripts that explore theories related to both risk of perpetration and vulnerability to
victimization are welcome.
The submission deadline for first drafts is September 15, 2010. Manuscripts should not exceed
6,000 words, including references and tables. Manuscripts can be submitted through the journal’s
submission portal at http://www.apa.org/pubs/journals/vio. Please note in your cover letter that you
are submitting for the special issue.
Manuscripts for regular, full-length articles are also being accepted. Psychology of Violence
publishes articles on all types of violence and victimization, including but not limited to: sexual
violence, youth violence, child maltreatment, bullying, children’s exposure to violence, intimate
partner violence, suicide, homicide, workplace violence, international violence and prevention
efforts. Manuscripts addressing under-served or disenfranchised groups are particularly welcome.
More information about the journal can be found at: http://www.apa.org/pubs/journals/vio.
Inquiries regarding topic or scope for the special issue or for other manuscripts can be sent to
Sherry Hamby, Editor, at [email protected].